Overview

Dataset statistics

Number of variables34
Number of observations168712
Missing cells1175754
Missing cells (%)20.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory322.3 MiB
Average record size in memory2.0 KiB

Variable types

CAT32
NUM2

Warnings

FILE# has a high cardinality: 168711 distinct values High cardinality
CRASH DATE has a high cardinality: 3815 distinct values High cardinality
CRASH TIME has a high cardinality: 1440 distinct values High cardinality
STREET NAME has a high cardinality: 2343 distinct values High cardinality
FORMATTED STREET has a high cardinality: 30093 distinct values High cardinality
CLOSEST STREET has a high cardinality: 7866 distinct values High cardinality
GEOLOCATION has a high cardinality: 32152 distinct values High cardinality
SUBZONE has 2666 (1.6%) missing values Missing
STREET DIRECTION has 120893 (71.7%) missing values Missing
STREET TYPE has 32953 (19.5%) missing values Missing
HIT&RUN has 137878 (81.7%) missing values Missing
TRAIN INVOLVED has 168640 (> 99.9%) missing values Missing
FATALITY has 168445 (99.8%) missing values Missing
INJURY has 152284 (90.3%) missing values Missing
PEDESTRIAN has 167722 (99.4%) missing values Missing
AT INTERSECTION has 106082 (62.9%) missing values Missing
CLOSEST STREET has 10617 (6.3%) missing values Missing
SECOND FACTOR has 104095 (61.7%) missing values Missing
TOT VEH is highly skewed (γ1 = 53.16523871) Skewed
FILE# is uniformly distributed Uniform

Reproduction

Analysis started2020-12-13 01:12:52.646048
Analysis finished2020-12-13 01:13:17.154138
Duration24.51 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

FILE#
Categorical

HIGH CARDINALITY
UNIFORM

Distinct168711
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
15-00003191
 
2
14-00004760
 
1
12-00014715
 
1
10-00010062
 
1
17-00001994
 
1
Other values (168706)
168706 
ValueCountFrequency (%) 
15-000031912< 0.1%
 
14-000047601< 0.1%
 
12-000147151< 0.1%
 
10-000100621< 0.1%
 
17-000019941< 0.1%
 
10-000065241< 0.1%
 
17-000153251< 0.1%
 
19-000107461< 0.1%
 
18-000127271< 0.1%
 
20-000037991< 0.1%
 
18-000163991< 0.1%
 
13-000083921< 0.1%
 
18-000022441< 0.1%
 
19-000143911< 0.1%
 
18-000021241< 0.1%
 
14-000115521< 0.1%
 
17-000180551< 0.1%
 
20-000040091< 0.1%
 
17-000119251< 0.1%
 
12-000136741< 0.1%
 
17-000153621< 0.1%
 
15-000070871< 0.1%
 
14-000002361< 0.1%
 
15-000027291< 0.1%
 
11-000047731< 0.1%
 
Other values (168686)168686> 99.9%
 
2020-12-12T20:13:17.537969image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique168710 ?
Unique (%)> 99.9%
2020-12-12T20:13:17.622541image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length11
Median length11
Mean length11
Min length11

Overview of Unicode Properties

Unique unicode characters11
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
069817437.6%
 
131530517.0%
 
-1687129.1%
 
2908464.9%
 
5867364.7%
 
4866644.7%
 
3861394.6%
 
6845954.6%
 
7823304.4%
 
8792474.3%
 
9770844.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number168712090.9%
 
Dash Punctuation1687129.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
069817441.4%
 
131530518.7%
 
2908465.4%
 
5867365.1%
 
4866645.1%
 
3861395.1%
 
6845955.0%
 
7823304.9%
 
8792474.7%
 
9770844.6%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-168712100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common1855832100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
069817437.6%
 
131530517.0%
 
-1687129.1%
 
2908464.9%
 
5867364.7%
 
4866644.7%
 
3861394.6%
 
6845954.6%
 
7823304.4%
 
8792474.3%
 
9770844.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1855832100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
069817437.6%
 
131530517.0%
 
-1687129.1%
 
2908464.9%
 
5867364.7%
 
4866644.7%
 
3861394.6%
 
6845954.6%
 
7823304.4%
 
8792474.3%
 
9770844.2%
 

CRASH DATE
Categorical

HIGH CARDINALITY

Distinct3815
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
05/09/2014
 
104
01/24/2014
 
102
09/16/2016
 
102
12/05/2016
 
98
09/02/2016
 
98
Other values (3810)
168208 
ValueCountFrequency (%) 
05/09/20141040.1%
 
01/24/20141020.1%
 
09/16/20161020.1%
 
12/05/2016980.1%
 
09/02/2016980.1%
 
12/19/2014980.1%
 
05/06/2016950.1%
 
03/21/2019950.1%
 
09/02/2011930.1%
 
09/30/2016920.1%
 
11/18/2016920.1%
 
05/01/2015910.1%
 
10/21/2016910.1%
 
11/03/2016910.1%
 
10/22/2016900.1%
 
12/13/2016900.1%
 
10/25/2019890.1%
 
05/08/2015890.1%
 
10/03/2016890.1%
 
03/04/2011890.1%
 
02/24/2017890.1%
 
03/03/2017880.1%
 
10/28/2016880.1%
 
05/10/2013870.1%
 
10/18/2016860.1%
 
Other values (3790)16639698.6%
 
2020-12-12T20:13:17.716622image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2020-12-12T20:13:17.798693image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

Overview of Unicode Properties

Unique unicode characters11
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
039242923.3%
 
/33742420.0%
 
132591019.3%
 
228721017.0%
 
3560423.3%
 
5493022.9%
 
6491012.9%
 
8482292.9%
 
7475792.8%
 
9474942.8%
 
4464002.8%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number134969680.0%
 
Other Punctuation33742420.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
039242929.1%
 
132591024.1%
 
228721021.3%
 
3560424.2%
 
5493023.7%
 
6491013.6%
 
8482293.6%
 
7475793.5%
 
9474943.5%
 
4464003.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/337424100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common1687120100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
039242923.3%
 
/33742420.0%
 
132591019.3%
 
228721017.0%
 
3560423.3%
 
5493022.9%
 
6491012.9%
 
8482292.9%
 
7475792.8%
 
9474942.8%
 
4464002.8%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1687120100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
039242923.3%
 
/33742420.0%
 
132591019.3%
 
228721017.0%
 
3560423.3%
 
5493022.9%
 
6491012.9%
 
8482292.9%
 
7475792.8%
 
9474942.8%
 
4464002.8%
 

CRASH TIME
Categorical

HIGH CARDINALITY

Distinct1440
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
05:00 PM
 
664
04:00 PM
 
649
03:00 PM
 
640
06:00 PM
 
579
04:30 PM
 
557
Other values (1435)
165623 
ValueCountFrequency (%) 
05:00 PM6640.4%
 
04:00 PM6490.4%
 
03:00 PM6400.4%
 
06:00 PM5790.3%
 
04:30 PM5570.3%
 
05:30 PM5550.3%
 
08:00 AM5350.3%
 
01:00 PM5310.3%
 
03:30 PM5270.3%
 
02:00 PM5110.3%
 
12:00 PM5010.3%
 
02:30 PM4360.3%
 
09:00 AM4320.3%
 
08:30 AM4110.2%
 
12:30 PM4070.2%
 
05:20 PM4030.2%
 
11:00 AM3950.2%
 
05:15 PM3930.2%
 
10:00 AM3880.2%
 
04:45 PM3860.2%
 
01:30 PM3850.2%
 
03:15 PM3800.2%
 
03:45 PM3760.2%
 
05:50 PM3720.2%
 
04:50 PM3690.2%
 
Other values (1415)15693093.0%
 
2020-12-12T20:13:17.892273image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:17.977347image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length8
Mean length8
Min length8

Overview of Unicode Properties

Unique unicode characters15
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
020445115.1%
 
:16871212.5%
 
16871212.5%
 
M16871212.5%
 
P1149538.5%
 
11032177.6%
 
2697355.2%
 
5652894.8%
 
3589364.4%
 
4584124.3%
 
A537594.0%
 
8296022.2%
 
7295802.2%
 
6291032.2%
 
9265232.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number67484850.0%
 
Uppercase Letter33742425.0%
 
Other Punctuation16871212.5%
 
Space Separator16871212.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
020445130.3%
 
110321715.3%
 
26973510.3%
 
5652899.7%
 
3589368.7%
 
4584128.7%
 
8296024.4%
 
7295804.4%
 
6291034.3%
 
9265233.9%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
:168712100.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
168712100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
M16871250.0%
 
P11495334.1%
 
A5375915.9%
 

Most occurring scripts

ValueCountFrequency (%) 
Common101227275.0%
 
Latin33742425.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
020445120.2%
 
:16871216.7%
 
16871216.7%
 
110321710.2%
 
2697356.9%
 
5652896.4%
 
3589365.8%
 
4584125.8%
 
8296022.9%
 
7295802.9%
 
6291032.9%
 
9265232.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
M16871250.0%
 
P11495334.1%
 
A5375915.9%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1349696100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
020445115.1%
 
:16871212.5%
 
16871212.5%
 
M16871212.5%
 
P1149538.5%
 
11032177.6%
 
2697355.2%
 
5652894.8%
 
3589364.4%
 
4584124.3%
 
A537594.0%
 
8296022.2%
 
7295802.2%
 
6291032.2%
 
9265232.0%
 

TOT VEH
Real number (ℝ)

SKEWED

Distinct26
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.01633553
Minimum-2
Maximum97
Zeros14
Zeros (%)< 0.1%
Memory size1.3 MiB
2020-12-12T20:13:18.047907image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile1
Q12
median2
Q32
95-th percentile3
Maximum97
Range99
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6882267149
Coefficient of variation (CV)0.341325491
Kurtosis6145.020394
Mean2.01633553
Median Absolute Deviation (MAD)0
Skewness53.16523871
Sum340180
Variance0.473656011
MonotocityNot monotonic
2020-12-12T20:13:18.121971image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%) 
214277084.6%
 
1133017.9%
 
3106776.3%
 
415400.9%
 
52750.2%
 
667< 0.1%
 
717< 0.1%
 
2315< 0.1%
 
014< 0.1%
 
225< 0.1%
 
214< 0.1%
 
204< 0.1%
 
94< 0.1%
 
83< 0.1%
 
103< 0.1%
 
332< 0.1%
 
122< 0.1%
 
-21< 0.1%
 
971< 0.1%
 
291< 0.1%
 
301< 0.1%
 
411< 0.1%
 
621< 0.1%
 
911< 0.1%
 
921< 0.1%
 
ValueCountFrequency (%) 
-21< 0.1%
 
014< 0.1%
 
1133017.9%
 
214277084.6%
 
3106776.3%
 
415400.9%
 
52750.2%
 
667< 0.1%
 
717< 0.1%
 
83< 0.1%
 
ValueCountFrequency (%) 
971< 0.1%
 
921< 0.1%
 
911< 0.1%
 
621< 0.1%
 
411< 0.1%
 
332< 0.1%
 
301< 0.1%
 
291< 0.1%
 
2315< 0.1%
 
225< 0.1%
 

DISTRICT
Categorical

Distinct22
Distinct (%)< 0.1%
Missing17
Missing (%)< 0.1%
Memory size1.3 MiB
2
68824 
3
50608 
1
30156 
4
18677 
5
 
244
Other values (17)
 
186
ValueCountFrequency (%) 
26882440.8%
 
35060830.0%
 
13015617.9%
 
41867711.1%
 
52440.1%
 
648< 0.1%
 
E42< 0.1%
 
A18< 0.1%
 
717< 0.1%
 
F14< 0.1%
 
011< 0.1%
 
C10< 0.1%
 
I6< 0.1%
 
D5< 0.1%
 
U4< 0.1%
 
B3< 0.1%
 
S3< 0.1%
 
O1< 0.1%
 
G1< 0.1%
 
W1< 0.1%
 
R1< 0.1%
 
91< 0.1%
 
(Missing)17< 0.1%
 
2020-12-12T20:13:18.209046image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique5 ?
Unique (%)< 0.1%
2020-12-12T20:13:18.291617image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.000201527
Min length1

Overview of Unicode Properties

Unique unicode characters24
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
26882440.8%
 
35060830.0%
 
13015617.9%
 
41867711.1%
 
52440.1%
 
648< 0.1%
 
E42< 0.1%
 
n34< 0.1%
 
A18< 0.1%
 
717< 0.1%
 
a17< 0.1%
 
F14< 0.1%
 
011< 0.1%
 
C10< 0.1%
 
I6< 0.1%
 
D5< 0.1%
 
U4< 0.1%
 
S3< 0.1%
 
B3< 0.1%
 
W1< 0.1%
 
R1< 0.1%
 
91< 0.1%
 
O1< 0.1%
 
G1< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number16858699.9%
 
Uppercase Letter1090.1%
 
Lowercase Letter51< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
26882440.8%
 
35060830.0%
 
13015617.9%
 
41867711.1%
 
52440.1%
 
648< 0.1%
 
717< 0.1%
 
011< 0.1%
 
91< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E4238.5%
 
A1816.5%
 
F1412.8%
 
C109.2%
 
I65.5%
 
D54.6%
 
U43.7%
 
S32.8%
 
B32.8%
 
W10.9%
 
R10.9%
 
O10.9%
 
G10.9%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n3466.7%
 
a1733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common16858699.9%
 
Latin1600.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
26882440.8%
 
35060830.0%
 
13015617.9%
 
41867711.1%
 
52440.1%
 
648< 0.1%
 
717< 0.1%
 
011< 0.1%
 
91< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E4226.2%
 
n3421.2%
 
A1811.2%
 
a1710.6%
 
F148.8%
 
C106.2%
 
I63.8%
 
D53.1%
 
U42.5%
 
S31.9%
 
B31.9%
 
W10.6%
 
R10.6%
 
O10.6%
 
G10.6%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII168746100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
26882440.8%
 
35060830.0%
 
13015617.9%
 
41867711.1%
 
52440.1%
 
648< 0.1%
 
E42< 0.1%
 
n34< 0.1%
 
A18< 0.1%
 
717< 0.1%
 
a17< 0.1%
 
F14< 0.1%
 
011< 0.1%
 
C10< 0.1%
 
I6< 0.1%
 
D5< 0.1%
 
U4< 0.1%
 
S3< 0.1%
 
B3< 0.1%
 
W1< 0.1%
 
R1< 0.1%
 
91< 0.1%
 
O1< 0.1%
 
G1< 0.1%
 

ZONE
Categorical

Distinct29
Distinct (%)< 0.1%
Missing1625
Missing (%)1.0%
Memory size1.3 MiB
B
37789 
C
27161 
A
25175 
D
23416 
F
21999 
Other values (24)
31547 
ValueCountFrequency (%) 
B3778922.4%
 
C2716116.1%
 
A2517514.9%
 
D2341613.9%
 
F2199913.0%
 
E2066512.2%
 
G104246.2%
 
H1020.1%
 
360< 0.1%
 
159< 0.1%
 
250< 0.1%
 
/46< 0.1%
 
943< 0.1%
 
018< 0.1%
 
714< 0.1%
 
512< 0.1%
 
412< 0.1%
 
S8< 0.1%
 
68< 0.1%
 
87< 0.1%
 
P4< 0.1%
 
R4< 0.1%
 
T2< 0.1%
 
N2< 0.1%
 
`2< 0.1%
 
Other values (4)5< 0.1%
 
(Missing)16251.0%
 
2020-12-12T20:13:18.379693image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2020-12-12T20:13:18.462264image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.019263597
Min length1

Overview of Unicode Properties

Unique unicode characters31
Unique unicode categories6 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
B3778922.0%
 
C2716115.8%
 
A2517514.6%
 
D2341613.6%
 
F2199912.8%
 
E2066512.0%
 
G104246.1%
 
n32501.9%
 
a16250.9%
 
H1020.1%
 
360< 0.1%
 
159< 0.1%
 
250< 0.1%
 
/46< 0.1%
 
943< 0.1%
 
018< 0.1%
 
714< 0.1%
 
412< 0.1%
 
512< 0.1%
 
68< 0.1%
 
S8< 0.1%
 
87< 0.1%
 
R4< 0.1%
 
P4< 0.1%
 
K2< 0.1%
 
Other values (6)9< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter16675597.0%
 
Lowercase Letter48752.8%
 
Decimal Number2830.2%
 
Other Punctuation46< 0.1%
 
Modifier Symbol2< 0.1%
 
Dash Punctuation1< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
B3778922.7%
 
C2716116.3%
 
A2517515.1%
 
D2341614.0%
 
F2199913.2%
 
E2066512.4%
 
G104246.3%
 
H1020.1%
 
S8< 0.1%
 
R4< 0.1%
 
P4< 0.1%
 
K2< 0.1%
 
N2< 0.1%
 
T2< 0.1%
 
W1< 0.1%
 
V1< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n325066.7%
 
a162533.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
36021.2%
 
15920.8%
 
25017.7%
 
94315.2%
 
0186.4%
 
7144.9%
 
4124.2%
 
5124.2%
 
682.8%
 
872.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/46100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`2100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-1100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin17163099.8%
 
Common3320.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
B3778922.0%
 
C2716115.8%
 
A2517514.7%
 
D2341613.6%
 
F2199912.8%
 
E2066512.0%
 
G104246.1%
 
n32501.9%
 
a16250.9%
 
H1020.1%
 
S8< 0.1%
 
R4< 0.1%
 
P4< 0.1%
 
K2< 0.1%
 
N2< 0.1%
 
T2< 0.1%
 
W1< 0.1%
 
V1< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
36018.1%
 
15917.8%
 
25015.1%
 
/4613.9%
 
94313.0%
 
0185.4%
 
7144.2%
 
4123.6%
 
5123.6%
 
682.4%
 
872.1%
 
`20.6%
 
-10.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII171962100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
B3778922.0%
 
C2716115.8%
 
A2517514.6%
 
D2341613.6%
 
F2199912.8%
 
E2066512.0%
 
G104246.1%
 
n32501.9%
 
a16250.9%
 
H1020.1%
 
360< 0.1%
 
159< 0.1%
 
250< 0.1%
 
/46< 0.1%
 
943< 0.1%
 
018< 0.1%
 
714< 0.1%
 
412< 0.1%
 
512< 0.1%
 
68< 0.1%
 
S8< 0.1%
 
87< 0.1%
 
R4< 0.1%
 
P4< 0.1%
 
K2< 0.1%
 
Other values (6)9< 0.1%
 

SUBZONE
Categorical

MISSING

Distinct29
Distinct (%)< 0.1%
Missing2666
Missing (%)1.6%
Memory size1.3 MiB
1
68893 
2
51060 
3
36279 
5
 
5916
4
 
3662
Other values (24)
 
236
ValueCountFrequency (%) 
16889340.8%
 
25106030.3%
 
33627921.5%
 
559163.5%
 
436622.2%
 
047< 0.1%
 
C32< 0.1%
 
E32< 0.1%
 
A31< 0.1%
 
B17< 0.1%
 
D14< 0.1%
 
711< 0.1%
 
69< 0.1%
 
Q7< 0.1%
 
-5< 0.1%
 
F5< 0.1%
 
`5< 0.1%
 
S4< 0.1%
 
H3< 0.1%
 
G2< 0.1%
 
!2< 0.1%
 
82< 0.1%
 
I2< 0.1%
 
R1< 0.1%
 
N1< 0.1%
 
Other values (4)4< 0.1%
 
(Missing)26661.6%
 
2020-12-12T20:13:18.552842image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6 ?
Unique (%)< 0.1%
2020-12-12T20:13:18.634912image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.031604154
Min length1

Overview of Unicode Properties

Unique unicode characters31
Unique unicode categories6 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
16889339.6%
 
25106029.3%
 
33627920.8%
 
559163.4%
 
n53323.1%
 
436622.1%
 
a26661.5%
 
047< 0.1%
 
E32< 0.1%
 
C32< 0.1%
 
A31< 0.1%
 
B17< 0.1%
 
D14< 0.1%
 
711< 0.1%
 
69< 0.1%
 
Q7< 0.1%
 
`5< 0.1%
 
F5< 0.1%
 
-5< 0.1%
 
S4< 0.1%
 
H3< 0.1%
 
!2< 0.1%
 
G2< 0.1%
 
I2< 0.1%
 
82< 0.1%
 
Other values (6)6< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number16587995.3%
 
Lowercase Letter79984.6%
 
Uppercase Letter1530.1%
 
Modifier Symbol5< 0.1%
 
Dash Punctuation5< 0.1%
 
Other Punctuation4< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
16889341.5%
 
25106030.8%
 
33627921.9%
 
559163.6%
 
436622.2%
 
047< 0.1%
 
711< 0.1%
 
69< 0.1%
 
82< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n533266.7%
 
a266633.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E3220.9%
 
C3220.9%
 
A3120.3%
 
B1711.1%
 
D149.2%
 
Q74.6%
 
F53.3%
 
S42.6%
 
H32.0%
 
G21.3%
 
I21.3%
 
N10.7%
 
W10.7%
 
R10.7%
 
V10.7%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
!250.0%
 
;125.0%
 
@125.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`5100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-5100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common16589395.3%
 
Latin81514.7%
 

Most frequent Common characters

ValueCountFrequency (%) 
16889341.5%
 
25106030.8%
 
33627921.9%
 
559163.6%
 
436622.2%
 
047< 0.1%
 
711< 0.1%
 
69< 0.1%
 
`5< 0.1%
 
-5< 0.1%
 
!2< 0.1%
 
82< 0.1%
 
;1< 0.1%
 
@1< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n533265.4%
 
a266632.7%
 
E320.4%
 
C320.4%
 
A310.4%
 
B170.2%
 
D140.2%
 
Q70.1%
 
F50.1%
 
S4< 0.1%
 
H3< 0.1%
 
G2< 0.1%
 
I2< 0.1%
 
N1< 0.1%
 
W1< 0.1%
 
R1< 0.1%
 
V1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII174044100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
16889339.6%
 
25106029.3%
 
33627920.8%
 
559163.4%
 
n53323.1%
 
436622.1%
 
a26661.5%
 
047< 0.1%
 
E32< 0.1%
 
C32< 0.1%
 
A31< 0.1%
 
B17< 0.1%
 
D14< 0.1%
 
711< 0.1%
 
69< 0.1%
 
Q7< 0.1%
 
`5< 0.1%
 
F5< 0.1%
 
-5< 0.1%
 
S4< 0.1%
 
H3< 0.1%
 
!2< 0.1%
 
G2< 0.1%
 
I2< 0.1%
 
82< 0.1%
 
Other values (6)6< 0.1%
 

STREET#
Real number (ℝ≥0)

Distinct6019
Distinct (%)3.6%
Missing1620
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean4339.487342
Minimum1
Maximum99999
Zeros0
Zeros (%)0.0%
Memory size1.3 MiB
2020-12-12T20:13:18.723989image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile264.55
Q11100
median3300
Q37001
95-th percentile11200
Maximum99999
Range99998
Interquartile range (IQR)5901

Descriptive statistics

Standard deviation3732.615523
Coefficient of variation (CV)0.860151264
Kurtosis19.69638384
Mean4339.487342
Median Absolute Deviation (MAD)2500
Skewness1.72044656
Sum725093619
Variance13932418.64
MonotocityNot monotonic
2020-12-12T20:13:18.812065image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
50048332.9%
 
10047702.8%
 
70046382.7%
 
80042172.5%
 
90038682.3%
 
60036162.1%
 
30031351.9%
 
100029651.8%
 
40026261.6%
 
20024631.5%
 
240021911.3%
 
450021471.3%
 
110019471.2%
 
500019381.1%
 
330019311.1%
 
220018731.1%
 
120018191.1%
 
260018021.1%
 
180017061.0%
 
190016781.0%
 
140016181.0%
 
230014870.9%
 
210014200.8%
 
130013990.8%
 
290013690.8%
 
Other values (5994)10363661.4%
 
(Missing)16201.0%
 
ValueCountFrequency (%) 
14< 0.1%
 
31< 0.1%
 
54< 0.1%
 
61< 0.1%
 
71< 0.1%
 
107< 0.1%
 
111< 0.1%
 
121< 0.1%
 
151< 0.1%
 
161< 0.1%
 
ValueCountFrequency (%) 
999991< 0.1%
 
940001< 0.1%
 
900001< 0.1%
 
890011< 0.1%
 
870001< 0.1%
 
840003< 0.1%
 
830001< 0.1%
 
800091< 0.1%
 
800001< 0.1%
 
766111< 0.1%
 

STREET DIRECTION
Categorical

MISSING

Distinct7
Distinct (%)< 0.1%
Missing120893
Missing (%)71.7%
Memory size1.3 MiB
S
15126 
N
11855 
W
10582 
E
10249 
SW
 
3
Other values (2)
 
4
ValueCountFrequency (%) 
S151269.0%
 
N118557.0%
 
W105826.3%
 
E102496.1%
 
SW3< 0.1%
 
SE2< 0.1%
 
NE2< 0.1%
 
(Missing)12089371.7%
 
2020-12-12T20:13:18.900641image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:18.953186image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:19.024248image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.433170136
Min length1

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n24178658.9%
 
a12089329.4%
 
S151313.7%
 
N118572.9%
 
W105852.6%
 
E102532.5%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter36267988.3%
 
Uppercase Letter4782611.7%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n24178666.7%
 
a12089333.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S1513131.6%
 
N1185724.8%
 
W1058522.1%
 
E1025321.4%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin410505100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n24178658.9%
 
a12089329.4%
 
S151313.7%
 
N118572.9%
 
W105852.6%
 
E102532.5%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII410505100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n24178658.9%
 
a12089329.4%
 
S151313.7%
 
N118572.9%
 
W105852.6%
 
E102532.5%
 

STREET NAME
Categorical

HIGH CARDINALITY

Distinct2343
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
AIRLINE
 
11978
I10
 
11711
FLORIDA
 
11043
SHERWOOD FOREST
 
7466
I12
 
5537
Other values (2338)
120977 
ValueCountFrequency (%) 
AIRLINE119787.1%
 
I10117116.9%
 
FLORIDA110436.5%
 
SHERWOOD FOREST74664.4%
 
I1255373.3%
 
I11054513.2%
 
GOVERNMENT47742.8%
 
PERKINS44382.6%
 
COLLEGE44362.6%
 
PLANK40462.4%
 
ESSEN39822.4%
 
GREENWELL SPRINGS35612.1%
 
HIGHLAND35242.1%
 
JEFFERSON33642.0%
 
LEE32351.9%
 
FOSTER31111.8%
 
NICHOLSON27361.6%
 
SCENIC26811.6%
 
ACADIAN26171.6%
 
CHOCTAW25591.5%
 
OLD HAMMOND23111.4%
 
COURSEY19671.2%
 
NORTH18751.1%
 
HARDING17721.1%
 
BURBANK15620.9%
 
Other values (2318)5697533.8%
 
2020-12-12T20:13:19.117828image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique777 ?
Unique (%)0.5%
2020-12-12T20:13:19.204403image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length26
Median length7
Mean length7.407232443
Min length1

Overview of Unicode Properties

Unique unicode characters44
Unique unicode categories7 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
E13647210.9%
 
I1046888.4%
 
O1044368.4%
 
R1032408.3%
 
N995498.0%
 
L889027.1%
 
A840606.7%
 
S691725.5%
 
D512604.1%
 
T449743.6%
 
H402183.2%
 
C350242.8%
 
F333152.7%
 
1324702.6%
 
G307982.5%
 
273192.2%
 
W248422.0%
 
P201751.6%
 
0191201.5%
 
M185401.5%
 
K142691.1%
 
B128971.0%
 
U126461.0%
 
Y109570.9%
 
V103840.8%
 
Other values (19)199621.6%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter115641792.5%
 
Decimal Number643365.1%
 
Space Separator273192.2%
 
Dash Punctuation9200.1%
 
Other Punctuation6850.1%
 
Open Punctuation6< 0.1%
 
Close Punctuation6< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E13647211.8%
 
I1046889.1%
 
O1044369.0%
 
R1032408.9%
 
N995498.6%
 
L889027.7%
 
A840607.3%
 
S691726.0%
 
D512604.4%
 
T449743.9%
 
H402183.5%
 
C350243.0%
 
F333152.9%
 
G307982.7%
 
W248422.1%
 
P201751.7%
 
M185401.6%
 
K142691.2%
 
B128971.1%
 
U126461.1%
 
Y109570.9%
 
V103840.9%
 
J43450.4%
 
X7730.1%
 
Q317< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
27319100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
13247050.5%
 
01912029.7%
 
2813712.6%
 
911901.8%
 
37801.2%
 
76561.0%
 
86110.9%
 
45230.8%
 
64630.7%
 
53860.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
'58184.8%
 
.9413.7%
 
/71.0%
 
,30.4%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(6100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)6100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-920100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin115641792.5%
 
Common932727.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E13647211.8%
 
I1046889.1%
 
O1044369.0%
 
R1032408.9%
 
N995498.6%
 
L889027.7%
 
A840607.3%
 
S691726.0%
 
D512604.4%
 
T449743.9%
 
H402183.5%
 
C350243.0%
 
F333152.9%
 
G307982.7%
 
W248422.1%
 
P201751.7%
 
M185401.6%
 
K142691.2%
 
B128971.1%
 
U126461.1%
 
Y109570.9%
 
V103840.9%
 
J43450.4%
 
X7730.1%
 
Q317< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
13247034.8%
 
2731929.3%
 
01912020.5%
 
281378.7%
 
911901.3%
 
-9201.0%
 
37800.8%
 
76560.7%
 
86110.7%
 
'5810.6%
 
45230.6%
 
64630.5%
 
53860.4%
 
.940.1%
 
/7< 0.1%
 
(6< 0.1%
 
)6< 0.1%
 
,3< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1249689100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
E13647210.9%
 
I1046888.4%
 
O1044368.4%
 
R1032408.3%
 
N995498.0%
 
L889027.1%
 
A840606.7%
 
S691725.5%
 
D512604.1%
 
T449743.6%
 
H402183.2%
 
C350242.8%
 
F333152.7%
 
1324702.6%
 
G307982.5%
 
273192.2%
 
W248422.0%
 
P201751.6%
 
0191201.5%
 
M185401.5%
 
K142691.1%
 
B128971.0%
 
U126461.0%
 
Y109570.9%
 
V103840.8%
 
Other values (19)199621.6%
 

STREET TYPE
Categorical

MISSING

Distinct15
Distinct (%)< 0.1%
Missing32953
Missing (%)19.5%
Memory size1.3 MiB
HW
28854 
BL
25294 
DR
24247 
RD
19406 
ST
19064 
Other values (10)
18894 
ValueCountFrequency (%) 
HW2885417.1%
 
BL2529415.0%
 
DR2424714.4%
 
RD1940611.5%
 
ST1906411.3%
 
AV79974.7%
 
LN70494.2%
 
TH25231.5%
 
PL5010.3%
 
OT4450.3%
 
CT1890.1%
 
PK960.1%
 
BT65< 0.1%
 
CR24< 0.1%
 
WY5< 0.1%
 
(Missing)3295319.5%
 
2020-12-12T20:13:19.286974image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:19.361037image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length2
Mean length2.19532102
Min length2

Overview of Unicode Properties

Unique unicode characters18
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n6590617.8%
 
R4367711.8%
 
D4365311.8%
 
a329538.9%
 
L328448.9%
 
H313778.5%
 
W288597.8%
 
B253596.8%
 
T222866.0%
 
S190645.1%
 
A79972.2%
 
V79972.2%
 
N70491.9%
 
P5970.2%
 
O4450.1%
 
C2130.1%
 
K96< 0.1%
 
Y5< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter27151873.3%
 
Lowercase Letter9885926.7%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
R4367716.1%
 
D4365316.1%
 
L3284412.1%
 
H3137711.6%
 
W2885910.6%
 
B253599.3%
 
T222868.2%
 
S190647.0%
 
A79972.9%
 
V79972.9%
 
N70492.6%
 
P5970.2%
 
O4450.2%
 
C2130.1%
 
K96< 0.1%
 
Y5< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n6590666.7%
 
a3295333.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin370377100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n6590617.8%
 
R4367711.8%
 
D4365311.8%
 
a329538.9%
 
L328448.9%
 
H313778.5%
 
W288597.8%
 
B253596.8%
 
T222866.0%
 
S190645.1%
 
A79972.2%
 
V79972.2%
 
N70491.9%
 
P5970.2%
 
O4450.1%
 
C2130.1%
 
K96< 0.1%
 
Y5< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII370377100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n6590617.8%
 
R4367711.8%
 
D4365311.8%
 
a329538.9%
 
L328448.9%
 
H313778.5%
 
W288597.8%
 
B253596.8%
 
T222866.0%
 
S190645.1%
 
A79972.2%
 
V79972.2%
 
N70491.9%
 
P5970.2%
 
O4450.1%
 
C2130.1%
 
K96< 0.1%
 
Y5< 0.1%
 

FORMATTED STREET
Categorical

HIGH CARDINALITY

Distinct30093
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
800 W I10
 
653
9700 AIRLINE HW
 
636
2600 COLLEGE DR
 
620
4500 ESSEN LN
 
546
700 E I12
 
485
Other values (30088)
165772 
ValueCountFrequency (%) 
800 W I106530.4%
 
9700 AIRLINE HW6360.4%
 
2600 COLLEGE DR6200.4%
 
4500 ESSEN LN5460.3%
 
700 E I124850.3%
 
9100 AIRLINE HW4840.3%
 
800 W I10 HW4610.3%
 
700 W I104580.3%
 
500 E I103950.2%
 
100 E I103850.2%
 
2400 S SHERWOOD FOREST BL3830.2%
 
1000 W I103690.2%
 
700 W I10 HW3680.2%
 
1200 W LEE DR3600.2%
 
900 E I103480.2%
 
7700 AIRLINE HW3470.2%
 
10000 AIRLINE HW3460.2%
 
100 W I103400.2%
 
800 E I123390.2%
 
10400 AIRLINE HW3380.2%
 
1800 S SHERWOOD FOREST BL3380.2%
 
2300 COLLEGE DR3250.2%
 
9300 FLORIDA BL3230.2%
 
500 W I103190.2%
 
2400 S ACADIAN TH3120.2%
 
Other values (30068)15843493.9%
 
2020-12-12T20:13:19.500657image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique17957 ?
Unique (%)10.6%
2020-12-12T20:13:19.594238image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length35
Median length16
Mean length15.91051022
Min length3

Overview of Unicode Properties

Unique unicode characters44
Unique unicode categories7 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
49812818.6%
 
032183412.0%
 
R1469175.5%
 
E1467255.5%
 
L1217464.5%
 
N1184554.4%
 
O1048813.9%
 
I1046883.9%
 
S1033673.9%
 
11004893.7%
 
D949133.5%
 
A920573.4%
 
H715952.7%
 
T672602.5%
 
W642862.4%
 
2519201.9%
 
5437241.6%
 
3392351.5%
 
B382561.4%
 
4364411.4%
 
C352371.3%
 
F333151.2%
 
G307981.1%
 
7304241.1%
 
9295171.1%
 
Other values (19)1580865.9%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter147576155.0%
 
Decimal Number70878826.4%
 
Space Separator49812818.6%
 
Dash Punctuation920< 0.1%
 
Other Punctuation685< 0.1%
 
Open Punctuation6< 0.1%
 
Close Punctuation6< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
032183445.4%
 
110048914.2%
 
2519207.3%
 
5437246.2%
 
3392355.5%
 
4364415.1%
 
7304244.3%
 
9295174.2%
 
6277223.9%
 
8274823.9%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
498128100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
R14691710.0%
 
E1467259.9%
 
L1217468.2%
 
N1184558.0%
 
O1048817.1%
 
I1046887.1%
 
S1033677.0%
 
D949136.4%
 
A920576.2%
 
H715954.9%
 
T672604.6%
 
W642864.4%
 
B382562.6%
 
C352372.4%
 
F333152.3%
 
G307982.1%
 
P207721.4%
 
M185401.3%
 
V183811.2%
 
K143651.0%
 
U126460.9%
 
Y109620.7%
 
J43450.3%
 
X7730.1%
 
Q317< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
'58184.8%
 
.9413.7%
 
/71.0%
 
,30.4%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(6100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)6100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-920100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin147576155.0%
 
Common120853345.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
49812841.2%
 
032183426.6%
 
11004898.3%
 
2519204.3%
 
5437243.6%
 
3392353.2%
 
4364413.0%
 
7304242.5%
 
9295172.4%
 
6277222.3%
 
8274822.3%
 
-9200.1%
 
'581< 0.1%
 
.94< 0.1%
 
/7< 0.1%
 
(6< 0.1%
 
)6< 0.1%
 
,3< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
R14691710.0%
 
E1467259.9%
 
L1217468.2%
 
N1184558.0%
 
O1048817.1%
 
I1046887.1%
 
S1033677.0%
 
D949136.4%
 
A920576.2%
 
H715954.9%
 
T672604.6%
 
W642864.4%
 
B382562.6%
 
C352372.4%
 
F333152.3%
 
G307982.1%
 
P207721.4%
 
M185401.3%
 
V183811.2%
 
K143651.0%
 
U126460.9%
 
Y109620.7%
 
J43450.3%
 
X7730.1%
 
Q317< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2684294100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
49812818.6%
 
032183412.0%
 
R1469175.5%
 
E1467255.5%
 
L1217464.5%
 
N1184554.4%
 
O1048813.9%
 
I1046883.9%
 
S1033673.9%
 
11004893.7%
 
D949133.5%
 
A920573.4%
 
H715952.7%
 
T672602.5%
 
W642862.4%
 
2519201.9%
 
5437241.6%
 
3392351.5%
 
B382561.4%
 
4364411.4%
 
C352371.3%
 
F333151.2%
 
G307981.1%
 
7304241.1%
 
9295171.1%
 
Other values (19)1580865.9%
 

OCCURED ON
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
CITY STREET
77257 
STATE HWY
31135 
INTERSTATE
24772 
U.S. HWY
18281 
OFF ROAD/ PRIVATE PROPERTY
16571 
Other values (2)
 
696
ValueCountFrequency (%) 
CITY STREET7725745.8%
 
STATE HWY3113518.5%
 
INTERSTATE2477214.7%
 
U.S. HWY1828110.8%
 
OFF ROAD/ PRIVATE PROPERTY165719.8%
 
PARISH ROAD6950.4%
 
TOLL ROAD1< 0.1%
 
2020-12-12T20:13:19.683315image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-12-12T20:13:19.739863image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:19.815929image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length26
Median length11
Mean length11.63230831
Min length8

Overview of Unicode Properties

Unique unicode characters21
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
T40150020.5%
 
E26833513.7%
 
1770829.0%
 
R1697048.6%
 
S1521407.8%
 
Y1432447.3%
 
I1192956.1%
 
A904404.6%
 
C772573.9%
 
O504102.6%
 
P504082.6%
 
H501112.6%
 
W494162.5%
 
.365621.9%
 
F331421.7%
 
N247721.3%
 
U182810.9%
 
D172670.9%
 
/165710.8%
 
V165710.8%
 
L2< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter173229588.3%
 
Space Separator1770829.0%
 
Other Punctuation531332.7%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
T40150023.2%
 
E26833515.5%
 
R1697049.8%
 
S1521408.8%
 
Y1432448.3%
 
I1192956.9%
 
A904405.2%
 
C772574.5%
 
O504102.9%
 
P504082.9%
 
H501112.9%
 
W494162.9%
 
F331421.9%
 
N247721.4%
 
U182811.1%
 
D172671.0%
 
V165711.0%
 
L2< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.3656268.8%
 
/1657131.2%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
177082100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin173229588.3%
 
Common23021511.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
T40150023.2%
 
E26833515.5%
 
R1697049.8%
 
S1521408.8%
 
Y1432448.3%
 
I1192956.9%
 
A904405.2%
 
C772574.5%
 
O504102.9%
 
P504082.9%
 
H501112.9%
 
W494162.9%
 
F331421.9%
 
N247721.4%
 
U182811.1%
 
D172671.0%
 
V165711.0%
 
L2< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
17708276.9%
 
.3656215.9%
 
/165717.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1962510100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
T40150020.5%
 
E26833513.7%
 
1770829.0%
 
R1697048.6%
 
S1521407.8%
 
Y1432447.3%
 
I1192956.1%
 
A904404.6%
 
C772573.9%
 
O504102.6%
 
P504082.6%
 
H501112.6%
 
W494162.5%
 
.365621.9%
 
F331421.7%
 
N247721.3%
 
U182810.9%
 
D172670.9%
 
/165710.8%
 
V165710.8%
 
L2< 0.1%
 

HIT&RUN
Categorical

MISSING

Distinct1
Distinct (%)< 0.1%
Missing137878
Missing (%)81.7%
Memory size1.3 MiB
X
30834 
ValueCountFrequency (%) 
X3083418.3%
 
(Missing)13787881.7%
 
2020-12-12T20:13:19.892995image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:19.937533image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:19.987576image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.63447769
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n27575662.0%
 
a13787831.0%
 
X308346.9%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter41363493.1%
 
Uppercase Letter308346.9%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n27575666.7%
 
a13787833.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
X30834100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin444468100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n27575662.0%
 
a13787831.0%
 
X308346.9%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII444468100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n27575662.0%
 
a13787831.0%
 
X308346.9%
 

TRAIN INVOLVED
Categorical

MISSING

Distinct1
Distinct (%)1.4%
Missing168640
Missing (%)> 99.9%
Memory size1.3 MiB
X
72 
ValueCountFrequency (%) 
X72< 0.1%
 
(Missing)168640> 99.9%
 
2020-12-12T20:13:20.062641image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:20.104177image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:20.154220image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.999146474
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n33728066.7%
 
a16864033.3%
 
X72< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter505920> 99.9%
 
Uppercase Letter72< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n33728066.7%
 
a16864033.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
X72100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin505992100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n33728066.7%
 
a16864033.3%
 
X72< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII505992100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n33728066.7%
 
a16864033.3%
 
X72< 0.1%
 

FATALITY
Categorical

MISSING

Distinct1
Distinct (%)0.4%
Missing168445
Missing (%)99.8%
Memory size1.3 MiB
X
267 
ValueCountFrequency (%) 
X2670.2%
 
(Missing)16844599.8%
 
2020-12-12T20:13:20.230285image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:20.272321image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:20.322865image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.996834843
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n33689066.6%
 
a16844533.3%
 
X2670.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter50533599.9%
 
Uppercase Letter2670.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n33689066.7%
 
a16844533.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
X267100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin505602100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n33689066.6%
 
a16844533.3%
 
X2670.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII505602100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n33689066.6%
 
a16844533.3%
 
X2670.1%
 

INJURY
Categorical

MISSING

Distinct1
Distinct (%)< 0.1%
Missing152284
Missing (%)90.3%
Memory size1.3 MiB
X
16428 
ValueCountFrequency (%) 
X164289.7%
 
(Missing)15228490.3%
 
2020-12-12T20:13:20.398430image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:20.445470image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:20.497515image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.805253924
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n30456864.4%
 
a15228432.2%
 
X164283.5%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter45685296.5%
 
Uppercase Letter164283.5%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n30456866.7%
 
a15228433.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
X16428100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin473280100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n30456864.4%
 
a15228432.2%
 
X164283.5%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII473280100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n30456864.4%
 
a15228432.2%
 
X164283.5%
 

PEDESTRIAN
Categorical

MISSING

Distinct1
Distinct (%)0.1%
Missing167722
Missing (%)99.4%
Memory size1.3 MiB
X
990 
ValueCountFrequency (%) 
X9900.6%
 
(Missing)16772299.4%
 
2020-12-12T20:13:20.573080image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:20.615617image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:20.666160image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.988264024
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n33544466.5%
 
a16772233.3%
 
X9900.2%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter50316699.8%
 
Uppercase Letter9900.2%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n33544466.7%
 
a16772233.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
X990100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin504156100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n33544466.5%
 
a16772233.3%
 
X9900.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII504156100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n33544466.5%
 
a16772233.3%
 
X9900.2%
 

AT INTERSECTION
Categorical

MISSING

Distinct1
Distinct (%)< 0.1%
Missing106082
Missing (%)62.9%
Memory size1.3 MiB
X
62630 
ValueCountFrequency (%) 
X6263037.1%
 
(Missing)10608262.9%
 
2020-12-12T20:13:20.741225image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:20.784763image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:20.832804image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.25755133
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n21216455.7%
 
a10608227.9%
 
X6263016.4%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter31824683.6%
 
Uppercase Letter6263016.4%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
X62630100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n21216466.7%
 
a10608233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin380876100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n21216455.7%
 
a10608227.9%
 
X6263016.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII380876100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n21216455.7%
 
a10608227.9%
 
X6263016.4%
 

CLOSEST STREET
Categorical

HIGH CARDINALITY
MISSING

Distinct7866
Distinct (%)5.0%
Missing10617
Missing (%)6.3%
Memory size1.3 MiB
AIRLINE HW
 
3116
COLLEGE DR
 
2467
SHERWOOD FOREST BL
 
2297
FLORIDA BL
 
2155
ESSEN LN
 
2138
Other values (7861)
145922 
ValueCountFrequency (%) 
AIRLINE HW31161.8%
 
COLLEGE DR24671.5%
 
SHERWOOD FOREST BL22971.4%
 
FLORIDA BL21551.3%
 
ESSEN LN21381.3%
 
I1018841.1%
 
PERKINS RD17951.1%
 
OLD HAMMOND HW17911.1%
 
I1214290.8%
 
ACADIAN TH14170.8%
 
CHOCTAW DR13330.8%
 
PLANK RD13320.8%
 
FOSTER DR13180.8%
 
GOVERNMENT ST12760.8%
 
HIGHLAND RD12350.7%
 
ESSEN11970.7%
 
ACADIAN11670.7%
 
COLLEGE11500.7%
 
GOODWOOD BL10820.6%
 
NICHOLSON DR10780.6%
 
SHERWOOD FOREST10600.6%
 
HARDING BL10400.6%
 
I1109950.6%
 
LEE DR9610.6%
 
COURSEY BL9450.6%
 
Other values (7841)12043771.4%
 
(Missing)106176.3%
 
2020-12-12T20:13:20.938895image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3228 ?
Unique (%)2.0%
2020-12-12T20:13:21.030974image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length29
Median length9
Mean length9.185979658
Min length2

Overview of Unicode Properties

Unique unicode characters48
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
E1358368.8%
 
R1267538.2%
 
1241648.0%
 
L1098027.1%
 
O1079547.0%
 
A1065086.9%
 
N978106.3%
 
D883405.7%
 
S864265.6%
 
T825875.3%
 
I754554.9%
 
H532623.4%
 
C457323.0%
 
W363982.3%
 
B333102.1%
 
M277181.8%
 
G270561.7%
 
P215761.4%
 
n212341.4%
 
V207671.3%
 
U198541.3%
 
F194701.3%
 
Y175741.1%
 
K162181.0%
 
1112530.7%
 
Other values (23)367282.4%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter136321688.0%
 
Space Separator1241648.0%
 
Lowercase Letter318512.1%
 
Decimal Number292851.9%
 
Other Punctuation8340.1%
 
Dash Punctuation426< 0.1%
 
Open Punctuation5< 0.1%
 
Close Punctuation4< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E13583610.0%
 
R1267539.3%
 
L1098028.1%
 
O1079547.9%
 
A1065087.8%
 
N978107.2%
 
D883406.5%
 
S864266.3%
 
T825876.1%
 
I754555.5%
 
H532623.9%
 
C457323.4%
 
W363982.7%
 
B333102.4%
 
M277182.0%
 
G270562.0%
 
P215761.6%
 
V207671.5%
 
U198541.5%
 
F194701.4%
 
Y175741.3%
 
K162181.2%
 
J38260.3%
 
X11640.1%
 
Q10650.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
124164100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
11125338.4%
 
2611720.9%
 
0523117.9%
 
913374.6%
 
712124.1%
 
39733.3%
 
89523.3%
 
57762.6%
 
47182.5%
 
67162.4%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n2123466.7%
 
a1061733.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
'51661.9%
 
.27533.0%
 
/344.1%
 
,50.6%
 
#30.4%
 
@10.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-426100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(5100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)4100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin139506790.0%
 
Common15471810.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E1358369.7%
 
R1267539.1%
 
L1098027.9%
 
O1079547.7%
 
A1065087.6%
 
N978107.0%
 
D883406.3%
 
S864266.2%
 
T825875.9%
 
I754555.4%
 
H532623.8%
 
C457323.3%
 
W363982.6%
 
B333102.4%
 
M277182.0%
 
G270561.9%
 
P215761.5%
 
n212341.5%
 
V207671.5%
 
U198541.4%
 
F194701.4%
 
Y175741.3%
 
K162181.2%
 
a106170.8%
 
J38260.3%
 
Other values (3)29840.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
12416480.3%
 
1112537.3%
 
261174.0%
 
052313.4%
 
913370.9%
 
712120.8%
 
39730.6%
 
89520.6%
 
57760.5%
 
47180.5%
 
67160.5%
 
'5160.3%
 
-4260.3%
 
.2750.2%
 
/34< 0.1%
 
,5< 0.1%
 
(5< 0.1%
 
)4< 0.1%
 
#3< 0.1%
 
@1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1549785100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
E1358368.8%
 
R1267538.2%
 
1241648.0%
 
L1098027.1%
 
O1079547.0%
 
A1065086.9%
 
N978106.3%
 
D883405.7%
 
S864265.6%
 
T825875.3%
 
I754554.9%
 
H532623.4%
 
C457323.0%
 
W363982.3%
 
B333102.1%
 
M277181.8%
 
G270561.7%
 
P215761.4%
 
n212341.4%
 
V207671.3%
 
U198541.3%
 
F194701.3%
 
Y175741.1%
 
K162181.0%
 
1112530.7%
 
Other values (23)367282.4%
 
Distinct9
Distinct (%)< 0.1%
Missing217
Missing (%)0.1%
Memory size1.3 MiB
REAR END
65678 
OTHER
24831 
RIGHT ANGLE
24736 
SIDESWIPE SAME
24592 
LEFT TURN
10082 
Other values (4)
18576 
ValueCountFrequency (%) 
REAR END6567838.9%
 
OTHER2483114.7%
 
RIGHT ANGLE2473614.7%
 
SIDESWIPE SAME2459214.6%
 
LEFT TURN100826.0%
 
NON-COLLISION WITH MOTOR VEHICLE92425.5%
 
RIGHT TURN57973.4%
 
SIDESWIPE OPPOSITE19701.2%
 
HEAD-ON15670.9%
 
(Missing)2170.1%
 
2020-12-12T20:13:21.112545image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:21.165590image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:21.248662image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32
Median length8
Mean length10.41713097
Min length3

Overview of Unicode Properties

Unique unicode characters23
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
E29074216.5%
 
R21184112.1%
 
1605819.1%
 
N1355867.7%
 
I1225957.0%
 
A1165736.6%
 
T1017795.8%
 
D938075.3%
 
S889285.1%
 
O765484.4%
 
H754154.3%
 
L625443.6%
 
G552693.1%
 
W358042.0%
 
M338341.9%
 
P305021.7%
 
C184841.1%
 
U158790.9%
 
-108090.6%
 
F100820.6%
 
V92420.5%
 
n434< 0.1%
 
a217< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter158545490.2%
 
Space Separator1605819.1%
 
Dash Punctuation108090.6%
 
Lowercase Letter651< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E29074218.3%
 
R21184113.4%
 
N1355868.6%
 
I1225957.7%
 
A1165737.4%
 
T1017796.4%
 
D938075.9%
 
S889285.6%
 
O765484.8%
 
H754154.8%
 
L625443.9%
 
G552693.5%
 
W358042.3%
 
M338342.1%
 
P305021.9%
 
C184841.2%
 
U158791.0%
 
F100820.6%
 
V92420.6%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
160581100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-10809100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n43466.7%
 
a21733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin158610590.2%
 
Common1713909.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E29074218.3%
 
R21184113.4%
 
N1355868.5%
 
I1225957.7%
 
A1165737.3%
 
T1017796.4%
 
D938075.9%
 
S889285.6%
 
O765484.8%
 
H754154.8%
 
L625443.9%
 
G552693.5%
 
W358042.3%
 
M338342.1%
 
P305021.9%
 
C184841.2%
 
U158791.0%
 
F100820.6%
 
V92420.6%
 
n434< 0.1%
 
a217< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
16058193.7%
 
-108096.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1757495100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
E29074216.5%
 
R21184112.1%
 
1605819.1%
 
N1355867.7%
 
I1225957.0%
 
A1165736.6%
 
T1017795.8%
 
D938075.3%
 
S889285.1%
 
O765484.4%
 
H754154.3%
 
L625443.6%
 
G552693.1%
 
W358042.0%
 
M338341.9%
 
P305021.7%
 
C184841.1%
 
U158790.9%
 
-108090.6%
 
F100820.6%
 
V92420.5%
 
n434< 0.1%
 
a217< 0.1%
 
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
DRY
143556 
WET
23824 
UNKNOWN
 
602
OTHER
 
371
ICE
 
203
Other values (2)
 
156
ValueCountFrequency (%) 
DRY14355685.1%
 
WET2382414.1%
 
UNKNOWN6020.4%
 
OTHER3710.2%
 
ICE2030.1%
 
CONTAMINANT (SAND, MUD, DIRT, OIL, ETC.)880.1%
 
SNOW/SLUSH68< 0.1%
 
2020-12-12T20:13:21.325227image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:21.376272image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:21.453338image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length40
Median length3
Mean length3.040791408
Min length3

Overview of Unicode Properties

Unique unicode characters23
Unique unicode categories5 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
R14401528.1%
 
D14382028.0%
 
Y14355628.0%
 
T245474.8%
 
W244944.8%
 
E244864.8%
 
N22260.4%
 
O12170.2%
 
U7580.1%
 
K6020.1%
 
I4670.1%
 
4400.1%
 
H4390.1%
 
C3790.1%
 
,3520.1%
 
S2920.1%
 
A2640.1%
 
M176< 0.1%
 
L156< 0.1%
 
(88< 0.1%
 
.88< 0.1%
 
)88< 0.1%
 
/68< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter51189499.8%
 
Other Punctuation5080.1%
 
Space Separator4400.1%
 
Open Punctuation88< 0.1%
 
Close Punctuation88< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
R14401528.1%
 
D14382028.1%
 
Y14355628.0%
 
T245474.8%
 
W244944.8%
 
E244864.8%
 
N22260.4%
 
O12170.2%
 
U7580.1%
 
K6020.1%
 
I4670.1%
 
H4390.1%
 
C3790.1%
 
S2920.1%
 
A2640.1%
 
M176< 0.1%
 
L156< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
440100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(88100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,35269.3%
 
.8817.3%
 
/6813.4%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)88100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin51189499.8%
 
Common11240.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
R14401528.1%
 
D14382028.1%
 
Y14355628.0%
 
T245474.8%
 
W244944.8%
 
E244864.8%
 
N22260.4%
 
O12170.2%
 
U7580.1%
 
K6020.1%
 
I4670.1%
 
H4390.1%
 
C3790.1%
 
S2920.1%
 
A2640.1%
 
M176< 0.1%
 
L156< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
44039.1%
 
,35231.3%
 
(887.8%
 
.887.8%
 
)887.8%
 
/686.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII513018100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
R14401528.1%
 
D14382028.0%
 
Y14355628.0%
 
T245474.8%
 
W244944.8%
 
E244864.8%
 
N22260.4%
 
O12170.2%
 
U7580.1%
 
K6020.1%
 
I4670.1%
 
4400.1%
 
H4390.1%
 
C3790.1%
 
,3520.1%
 
S2920.1%
 
A2640.1%
 
M176< 0.1%
 
L156< 0.1%
 
(88< 0.1%
 
.88< 0.1%
 
)88< 0.1%
 
/68< 0.1%
 

SURFACE TYPE
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
CONCRETE
104528 
BLACK TOP
62963 
OTHER
 
576
GRAVEL
 
316
UNKNOWN
 
160
Other values (2)
 
169
ValueCountFrequency (%) 
CONCRETE10452862.0%
 
BLACK TOP6296337.3%
 
OTHER5760.3%
 
GRAVEL3160.2%
 
UNKNOWN1600.1%
 
DIRT1190.1%
 
BRICK50< 0.1%
 
2020-12-12T20:13:21.532406image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:21.580447image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:21.649006image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length8
Mean length8.354550951
Min length4

Overview of Unicode Properties

Unique unicode characters19
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
C27206919.3%
 
E20994814.9%
 
O16822711.9%
 
T16818611.9%
 
R1055897.5%
 
N1050087.4%
 
L632794.5%
 
A632794.5%
 
K631734.5%
 
B630134.5%
 
629634.5%
 
P629634.5%
 
H576< 0.1%
 
G316< 0.1%
 
V316< 0.1%
 
I169< 0.1%
 
U160< 0.1%
 
W160< 0.1%
 
D119< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter134655095.5%
 
Space Separator629634.5%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
C27206920.2%
 
E20994815.6%
 
O16822712.5%
 
T16818612.5%
 
R1055897.8%
 
N1050087.8%
 
L632794.7%
 
A632794.7%
 
K631734.7%
 
B630134.7%
 
P629634.7%
 
H576< 0.1%
 
G316< 0.1%
 
V316< 0.1%
 
I169< 0.1%
 
U160< 0.1%
 
W160< 0.1%
 
D119< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
62963100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin134655095.5%
 
Common629634.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
C27206920.2%
 
E20994815.6%
 
O16822712.5%
 
T16818612.5%
 
R1055897.8%
 
N1050087.8%
 
L632794.7%
 
A632794.7%
 
K631734.7%
 
B630134.7%
 
P629634.7%
 
H576< 0.1%
 
G316< 0.1%
 
V316< 0.1%
 
I169< 0.1%
 
U160< 0.1%
 
W160< 0.1%
 
D119< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
62963100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1409513100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
C27206919.3%
 
E20994814.9%
 
O16822711.9%
 
T16818611.9%
 
R1055897.5%
 
N1050087.4%
 
L632794.5%
 
A632794.5%
 
K631734.5%
 
B630134.5%
 
629634.5%
 
P629634.5%
 
H576< 0.1%
 
G316< 0.1%
 
V316< 0.1%
 
I169< 0.1%
 
U160< 0.1%
 
W160< 0.1%
 
D119< 0.1%
 

ROAD CONDITION
Categorical

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
NO ABNORMALITIES
163616 
WATER ON ROADWAY
 
1373
OTHER
 
1360
ROAD CONSTRUCTION, REPAIR
 
1016
SHOULDER ABNORMALITIES
 
657
Other values (9)
 
690
ValueCountFrequency (%) 
NO ABNORMALITIES16361697.0%
 
WATER ON ROADWAY13730.8%
 
OTHER13600.8%
 
ROAD CONSTRUCTION, REPAIR10160.6%
 
SHOULDER ABNORMALITIES6570.4%
 
OBJECT IN ROADWAY1910.1%
 
LOOSE SURFACE MATERIAL1430.1%
 
BUMPS1100.1%
 
HOLES940.1%
 
PREVIOUS CRASH77< 0.1%
 
ANIMAL IN ROADWAY24< 0.1%
 
CONSTRUCTION - NO WARNING21< 0.1%
 
DEEP RUTS19< 0.1%
 
OVERHEAD CLEARANCE LIMITED11< 0.1%
 
2020-12-12T20:13:21.727073image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:21.804640image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length26
Median length16
Mean length15.98202262
Min length5

Overview of Unicode Properties

Unique unicode characters25
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
O33663712.5%
 
A33573512.5%
 
N33164912.3%
 
I33110112.3%
 
R1738386.4%
 
1699486.3%
 
E1695636.3%
 
T1694446.3%
 
S1666306.2%
 
L1653566.1%
 
B1645746.1%
 
M1645616.1%
 
D33020.1%
 
W29820.1%
 
C25070.1%
 
H21990.1%
 
U20430.1%
 
Y15880.1%
 
P1222< 0.1%
 
,1016< 0.1%
 
J191< 0.1%
 
F143< 0.1%
 
V88< 0.1%
 
-21< 0.1%
 
G21< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter252537493.7%
 
Space Separator1699486.3%
 
Other Punctuation1016< 0.1%
 
Dash Punctuation21< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
O33663713.3%
 
A33573513.3%
 
N33164913.1%
 
I33110113.1%
 
R1738386.9%
 
E1695636.7%
 
T1694446.7%
 
S1666306.6%
 
L1653566.5%
 
B1645746.5%
 
M1645616.5%
 
D33020.1%
 
W29820.1%
 
C25070.1%
 
H21990.1%
 
U20430.1%
 
Y15880.1%
 
P1222< 0.1%
 
J191< 0.1%
 
F143< 0.1%
 
V88< 0.1%
 
G21< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
169948100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,1016100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-21100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin252537493.7%
 
Common1709856.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
O33663713.3%
 
A33573513.3%
 
N33164913.1%
 
I33110113.1%
 
R1738386.9%
 
E1695636.7%
 
T1694446.7%
 
S1666306.6%
 
L1653566.5%
 
B1645746.5%
 
M1645616.5%
 
D33020.1%
 
W29820.1%
 
C25070.1%
 
H21990.1%
 
U20430.1%
 
Y15880.1%
 
P1222< 0.1%
 
J191< 0.1%
 
F143< 0.1%
 
V88< 0.1%
 
G21< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
16994899.4%
 
,10160.6%
 
-21< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2696359100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
O33663712.5%
 
A33573512.5%
 
N33164912.3%
 
I33110112.3%
 
R1738386.4%
 
1699486.3%
 
E1695636.3%
 
T1694446.3%
 
S1666306.2%
 
L1653566.1%
 
B1645746.1%
 
M1645616.1%
 
D33020.1%
 
W29820.1%
 
C25070.1%
 
H21990.1%
 
U20430.1%
 
Y15880.1%
 
P1222< 0.1%
 
,1016< 0.1%
 
J191< 0.1%
 
F143< 0.1%
 
V88< 0.1%
 
-21< 0.1%
 
G21< 0.1%
 

ROAD TYPE
Categorical

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
TWO-WAY ROAD WITH NO PHYSICAL SEPARATION
81737 
TOW-WAY ROAD WITH A PHYSICAL SEPARATION
45563 
OTHER
16316 
ONE-WAY ROAD
14959 
TWO-WAY ROAD WITH A PHYSICAL BARRIER
9960 
ValueCountFrequency (%) 
TWO-WAY ROAD WITH NO PHYSICAL SEPARATION8173748.4%
 
TOW-WAY ROAD WITH A PHYSICAL SEPARATION4556327.0%
 
OTHER163169.7%
 
ONE-WAY ROAD149598.9%
 
TWO-WAY ROAD WITH A PHYSICAL BARRIER99605.9%
 
UNKNOWN1770.1%
 
2020-12-12T20:13:21.886210image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:21.941758image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:22.017323image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length40
Median length39
Mean length33.59170658
Min length5

Overview of Unicode Properties

Unique unicode characters20
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
A76178113.4%
 
70125912.4%
 
O5299689.4%
 
W4269167.5%
 
T4181367.4%
 
I4117807.3%
 
R3257155.7%
 
H2908365.1%
 
Y2894795.1%
 
P2645604.7%
 
S2645604.7%
 
N2245274.0%
 
E1685353.0%
 
-1522192.7%
 
D1522192.7%
 
C1372602.4%
 
L1372602.4%
 
B99600.2%
 
U177< 0.1%
 
K177< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter481384684.9%
 
Space Separator70125912.4%
 
Dash Punctuation1522192.7%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A76178115.8%
 
O52996811.0%
 
W4269168.9%
 
T4181368.7%
 
I4117808.6%
 
R3257156.8%
 
H2908366.0%
 
Y2894796.0%
 
P2645605.5%
 
S2645605.5%
 
N2245274.7%
 
E1685353.5%
 
D1522193.2%
 
C1372602.9%
 
L1372602.9%
 
B99600.2%
 
U177< 0.1%
 
K177< 0.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-152219100.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
701259100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin481384684.9%
 
Common85347815.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
A76178115.8%
 
O52996811.0%
 
W4269168.9%
 
T4181368.7%
 
I4117808.6%
 
R3257156.8%
 
H2908366.0%
 
Y2894796.0%
 
P2645605.5%
 
S2645605.5%
 
N2245274.7%
 
E1685353.5%
 
D1522193.2%
 
C1372602.9%
 
L1372602.9%
 
B99600.2%
 
U177< 0.1%
 
K177< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
70125982.2%
 
-15221917.8%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5667324100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
A76178113.4%
 
70125912.4%
 
O5299689.4%
 
W4269167.5%
 
T4181367.4%
 
I4117807.3%
 
R3257155.7%
 
H2908365.1%
 
Y2894795.1%
 
P2645604.7%
 
S2645604.7%
 
N2245274.0%
 
E1685353.0%
 
-1522192.7%
 
D1522192.7%
 
C1372602.4%
 
L1372602.4%
 
B99600.2%
 
U177< 0.1%
 
K177< 0.1%
 

ALIGNMENT
Categorical

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
STRAIGHT-LEVEL
157297 
STRAIGHT-LEVEL ELEVATED
 
4849
CURVE- LEFT
 
1909
OTHER
 
1712
ON GRADE-STRAIGHT
 
929
Other values (5)
 
2016
ValueCountFrequency (%) 
STRAIGHT-LEVEL15729793.2%
 
STRAIGHT-LEVEL ELEVATED48492.9%
 
CURVE- LEFT19091.1%
 
OTHER17121.0%
 
ON GRADE-STRAIGHT9290.6%
 
CURVE-LEVEL ELEVATED7480.4%
 
ON GRADE-CURVE4860.3%
 
HILLCREST-STRAIGHT4860.3%
 
UNKNOWN1990.1%
 
HILLCREST-CURVE970.1%
 
2020-12-12T20:13:22.098393image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:22.162949image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:22.260032image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length23
Median length14
Mean length14.18036061
Min length5

Overview of Unicode Properties

Unique unicode characters20
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
E35143814.7%
 
T33692314.1%
 
L33446014.0%
 
V1717317.2%
 
A1705737.1%
 
R1705117.1%
 
-1668017.0%
 
H1658566.9%
 
G1649766.9%
 
S1641446.9%
 
I1641446.9%
 
89210.4%
 
D70120.3%
 
C38230.2%
 
U34390.1%
 
O33260.1%
 
N20120.1%
 
F19090.1%
 
K199< 0.1%
 
W199< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter221667592.7%
 
Dash Punctuation1668017.0%
 
Space Separator89210.4%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E35143815.9%
 
T33692315.2%
 
L33446015.1%
 
V1717317.7%
 
A1705737.7%
 
R1705117.7%
 
H1658567.5%
 
G1649767.4%
 
S1641447.4%
 
I1641447.4%
 
D70120.3%
 
C38230.2%
 
U34390.2%
 
O33260.2%
 
N20120.1%
 
F19090.1%
 
K199< 0.1%
 
W199< 0.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-166801100.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
8921100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin221667592.7%
 
Common1757227.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E35143815.9%
 
T33692315.2%
 
L33446015.1%
 
V1717317.7%
 
A1705737.7%
 
R1705117.7%
 
H1658567.5%
 
G1649767.4%
 
S1641447.4%
 
I1641447.4%
 
D70120.3%
 
C38230.2%
 
U34390.2%
 
O33260.2%
 
N20120.1%
 
F19090.1%
 
K199< 0.1%
 
W199< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
-16680194.9%
 
89215.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2392397100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
E35143814.7%
 
T33692314.1%
 
L33446014.0%
 
V1717317.2%
 
A1705737.1%
 
R1705117.1%
 
-1668017.0%
 
H1658566.9%
 
G1649766.9%
 
S1641446.9%
 
I1641446.9%
 
89210.4%
 
D70120.3%
 
C38230.2%
 
U34390.1%
 
O33260.1%
 
N20120.1%
 
F19090.1%
 
K199< 0.1%
 
W199< 0.1%
 

PRIMARY FACTOR
Categorical

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
VIOLATIONS
136656 
MOVEMENT PRIOR TO CRASH
22397 
CONDITION OF DRIVER
 
5429
VEHICLE CONDITIONS
 
1181
ROADWAY CONDITION
 
609
Other values (8)
 
2440
ValueCountFrequency (%) 
VIOLATIONS13665681.0%
 
MOVEMENT PRIOR TO CRASH2239713.3%
 
CONDITION OF DRIVER54293.2%
 
VEHICLE CONDITIONS11810.7%
 
ROADWAY CONDITION6090.4%
 
VISION OBSCUREMENTS5860.3%
 
PEDESTRIAN ACTIONS5130.3%
 
ROAD SURFACE4500.3%
 
WEATHER3330.2%
 
KIND OF LOCATION2990.2%
 
TRAFFIC CONTROL1510.1%
 
CONDITION OF PEDESTRIAN63< 0.1%
 
LIGHTING45< 0.1%
 
2020-12-12T20:13:22.343604image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:22.421671image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length23
Median length10
Mean length12.17109631
Min length7

Overview of Unicode Properties

Unique unicode characters23
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
O36450217.8%
 
I31998315.6%
 
T1913869.3%
 
N1766728.6%
 
V1662498.1%
 
S1635318.0%
 
A1630437.9%
 
L1383326.7%
 
822634.0%
 
R813554.0%
 
E560252.7%
 
M453802.2%
 
C330101.6%
 
H239561.2%
 
P229731.1%
 
D146450.7%
 
F65430.3%
 
U10360.1%
 
W942< 0.1%
 
Y609< 0.1%
 
B586< 0.1%
 
K299< 0.1%
 
G90< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter197114796.0%
 
Space Separator822634.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
O36450218.5%
 
I31998316.2%
 
T1913869.7%
 
N1766729.0%
 
V1662498.4%
 
S1635318.3%
 
A1630438.3%
 
L1383327.0%
 
R813554.1%
 
E560252.8%
 
M453802.3%
 
C330101.7%
 
H239561.2%
 
P229731.2%
 
D146450.7%
 
F65430.3%
 
U10360.1%
 
W942< 0.1%
 
Y609< 0.1%
 
B586< 0.1%
 
K299< 0.1%
 
G90< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
82263100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin197114796.0%
 
Common822634.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
O36450218.5%
 
I31998316.2%
 
T1913869.7%
 
N1766729.0%
 
V1662498.4%
 
S1635318.3%
 
A1630438.3%
 
L1383327.0%
 
R813554.1%
 
E560252.8%
 
M453802.3%
 
C330101.7%
 
H239561.2%
 
P229731.2%
 
D146450.7%
 
F65430.3%
 
U10360.1%
 
W942< 0.1%
 
Y609< 0.1%
 
B586< 0.1%
 
K299< 0.1%
 
G90< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
82263100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2053410100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
O36450217.8%
 
I31998315.6%
 
T1913869.3%
 
N1766728.6%
 
V1662498.1%
 
S1635318.0%
 
A1630437.9%
 
L1383326.7%
 
822634.0%
 
R813554.0%
 
E560252.7%
 
M453802.2%
 
C330101.6%
 
H239561.2%
 
P229731.1%
 
D146450.7%
 
F65430.3%
 
U10360.1%
 
W942< 0.1%
 
Y609< 0.1%
 
B586< 0.1%
 
K299< 0.1%
 
G90< 0.1%
 

SECOND FACTOR
Categorical

MISSING

Distinct13
Distinct (%)< 0.1%
Missing104095
Missing (%)61.7%
Memory size1.3 MiB
MOVEMENT PRIOR TO CRASH
51219 
VIOLATIONS
9933 
CONDITION OF DRIVER
 
1800
VISION OBSCUREMENTS
 
344
WEATHER
 
286
Other values (8)
 
1035
ValueCountFrequency (%) 
MOVEMENT PRIOR TO CRASH5121930.4%
 
VIOLATIONS99335.9%
 
CONDITION OF DRIVER18001.1%
 
VISION OBSCUREMENTS3440.2%
 
WEATHER2860.2%
 
ROAD SURFACE2600.2%
 
VEHICLE CONDITIONS2150.1%
 
ROADWAY CONDITION1850.1%
 
KIND OF LOCATION1410.1%
 
PEDESTRIAN ACTIONS82< 0.1%
 
TRAFFIC CONTROL70< 0.1%
 
LIGHTING54< 0.1%
 
CONDITION OF PEDESTRIAN28< 0.1%
 
(Missing)10409561.7%
 
2020-12-12T20:13:22.503742image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:22.580308image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length23
Median length3
Mean length9.770395704
Min length3

Overview of Unicode Properties

Unique unicode characters25
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n20819012.6%
 
O18158511.0%
 
R1588429.6%
 
1587519.6%
 
T1157567.0%
 
E1064086.5%
 
a1040956.3%
 
M1027826.2%
 
I788964.8%
 
N668944.1%
 
V635113.9%
 
S628513.8%
 
A627313.8%
 
C546293.3%
 
H517743.1%
 
P513293.1%
 
L104130.6%
 
D47240.3%
 
F23690.1%
 
U604< 0.1%
 
W471< 0.1%
 
B344< 0.1%
 
Y185< 0.1%
 
K141< 0.1%
 
G108< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter117734771.4%
 
Lowercase Letter31228518.9%
 
Space Separator1587519.6%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n20819066.7%
 
a10409533.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
O18158515.4%
 
R15884213.5%
 
T1157569.8%
 
E1064089.0%
 
M1027828.7%
 
I788966.7%
 
N668945.7%
 
V635115.4%
 
S628515.3%
 
A627315.3%
 
C546294.6%
 
H517744.4%
 
P513294.4%
 
L104130.9%
 
D47240.4%
 
F23690.2%
 
U6040.1%
 
W471< 0.1%
 
B344< 0.1%
 
Y185< 0.1%
 
K141< 0.1%
 
G108< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
158751100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin148963290.4%
 
Common1587519.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n20819014.0%
 
O18158512.2%
 
R15884210.7%
 
T1157567.8%
 
E1064087.1%
 
a1040957.0%
 
M1027826.9%
 
I788965.3%
 
N668944.5%
 
V635114.3%
 
S628514.2%
 
A627314.2%
 
C546293.7%
 
H517743.5%
 
P513293.4%
 
L104130.7%
 
D47240.3%
 
F23690.2%
 
U604< 0.1%
 
W471< 0.1%
 
B344< 0.1%
 
Y185< 0.1%
 
K141< 0.1%
 
G108< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
158751100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1648383100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n20819012.6%
 
O18158511.0%
 
R1588429.6%
 
1587519.6%
 
T1157567.0%
 
E1064086.5%
 
a1040956.3%
 
M1027826.2%
 
I788964.8%
 
N668944.1%
 
V635113.9%
 
S628513.8%
 
A627313.8%
 
C546293.3%
 
H517743.1%
 
P513293.1%
 
L104130.6%
 
D47240.3%
 
F23690.1%
 
U604< 0.1%
 
W471< 0.1%
 
B344< 0.1%
 
Y185< 0.1%
 
K141< 0.1%
 
G108< 0.1%
 

WEATHER
Categorical

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
CLEAR
127422 
CLOUDY
22941 
RAIN
16755 
UNKNOWN
 
916
FOG/SMOKE
 
388
Other values (5)
 
290
ValueCountFrequency (%) 
CLEAR12742275.5%
 
CLOUDY2294113.6%
 
RAIN167559.9%
 
UNKNOWN9160.5%
 
FOG/SMOKE3880.2%
 
SLEET/HAIL1130.1%
 
OTHER990.1%
 
SNOW61< 0.1%
 
SEVERE CROSSWIND14< 0.1%
 
BLOWING SAND, SOIL, DIRT, SNOW3< 0.1%
 
2020-12-12T20:13:22.661878image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:22.715925image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:22.799997image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length30
Median length5
Mean length5.061068567
Min length4

Overview of Unicode Properties

Unique unicode characters24
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
L15059517.6%
 
C15037717.6%
 
R14430716.9%
 
A14429316.9%
 
E12817715.0%
 
O248162.9%
 
U238572.8%
 
D229612.7%
 
Y229412.7%
 
N195872.3%
 
I168912.0%
 
K13040.2%
 
W9970.1%
 
S6130.1%
 
/5010.1%
 
G391< 0.1%
 
F388< 0.1%
 
M388< 0.1%
 
T215< 0.1%
 
H212< 0.1%
 
26< 0.1%
 
V14< 0.1%
 
,9< 0.1%
 
B3< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter85332799.9%
 
Other Punctuation5100.1%
 
Space Separator26< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
L15059517.6%
 
C15037717.6%
 
R14430716.9%
 
A14429316.9%
 
E12817715.0%
 
O248162.9%
 
U238572.8%
 
D229612.7%
 
Y229412.7%
 
N195872.3%
 
I168912.0%
 
K13040.2%
 
W9970.1%
 
S6130.1%
 
G391< 0.1%
 
F388< 0.1%
 
M388< 0.1%
 
T215< 0.1%
 
H212< 0.1%
 
V14< 0.1%
 
B3< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/50198.2%
 
,91.8%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
26100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin85332799.9%
 
Common5360.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
L15059517.6%
 
C15037717.6%
 
R14430716.9%
 
A14429316.9%
 
E12817715.0%
 
O248162.9%
 
U238572.8%
 
D229612.7%
 
Y229412.7%
 
N195872.3%
 
I168912.0%
 
K13040.2%
 
W9970.1%
 
S6130.1%
 
G391< 0.1%
 
F388< 0.1%
 
M388< 0.1%
 
T215< 0.1%
 
H212< 0.1%
 
V14< 0.1%
 
B3< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
/50193.5%
 
264.9%
 
,91.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII853863100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
L15059517.6%
 
C15037717.6%
 
R14430716.9%
 
A14429316.9%
 
E12817715.0%
 
O248162.9%
 
U238572.8%
 
D229612.7%
 
Y229412.7%
 
N195872.3%
 
I168912.0%
 
K13040.2%
 
W9970.1%
 
S6130.1%
 
/5010.1%
 
G391< 0.1%
 
F388< 0.1%
 
M388< 0.1%
 
T215< 0.1%
 
H212< 0.1%
 
26< 0.1%
 
V14< 0.1%
 
,9< 0.1%
 
B3< 0.1%
 

LOCATION KIND
Categorical

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
BUSINESS CONTINUOUS
64626 
BUSINESS, MIXED RESIDENTIAL
62947 
RESIDENTIAL DISTRICT
21753 
OTHER
10413 
MANUFACTURING OF INDUSTRAIL
 
6458
Other values (3)
 
2515
ValueCountFrequency (%) 
BUSINESS CONTINUOUS6462638.3%
 
BUSINESS, MIXED RESIDENTIAL6294737.3%
 
RESIDENTIAL DISTRICT2175312.9%
 
OTHER104136.2%
 
MANUFACTURING OF INDUSTRAIL64583.8%
 
OPEN COUNTRY13320.8%
 
RESIDENTIAL SCATTERED8610.5%
 
SCHOOL OR PLAYGROUND3220.2%
 
2020-12-12T20:13:22.881067image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:22.934613image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:23.014181image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length27
Median length20
Mean length21.51274954
Min length5

Overview of Unicode Properties

Unique unicode characters22
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
S56230015.5%
 
I48914813.5%
 
E37510910.3%
 
N36474610.0%
 
U2778537.7%
 
2280266.3%
 
T2200766.1%
 
D1779024.9%
 
O1500754.1%
 
R1334803.7%
 
B1275733.5%
 
A1061182.9%
 
C953522.6%
 
L926632.6%
 
M694051.9%
 
,629471.7%
 
X629471.7%
 
F129160.4%
 
H107350.3%
 
G67800.2%
 
P1654< 0.1%
 
Y1654< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter333848692.0%
 
Space Separator2280266.3%
 
Other Punctuation629471.7%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S56230016.8%
 
I48914814.7%
 
E37510911.2%
 
N36474610.9%
 
U2778538.3%
 
T2200766.6%
 
D1779025.3%
 
O1500754.5%
 
R1334804.0%
 
B1275733.8%
 
A1061183.2%
 
C953522.9%
 
L926632.8%
 
M694052.1%
 
X629471.9%
 
F129160.4%
 
H107350.3%
 
G67800.2%
 
P1654< 0.1%
 
Y1654< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
228026100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,62947100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin333848692.0%
 
Common2909738.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
S56230016.8%
 
I48914814.7%
 
E37510911.2%
 
N36474610.9%
 
U2778538.3%
 
T2200766.6%
 
D1779025.3%
 
O1500754.5%
 
R1334804.0%
 
B1275733.8%
 
A1061183.2%
 
C953522.9%
 
L926632.8%
 
M694052.1%
 
X629471.9%
 
F129160.4%
 
H107350.3%
 
G67800.2%
 
P1654< 0.1%
 
Y1654< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
22802678.4%
 
,6294721.6%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII3629459100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
S56230015.5%
 
I48914813.5%
 
E37510910.3%
 
N36474610.0%
 
U2778537.7%
 
2280266.3%
 
T2200766.1%
 
D1779024.9%
 
O1500754.1%
 
R1334803.7%
 
B1275733.5%
 
A1061182.9%
 
C953522.6%
 
L926632.6%
 
M694051.9%
 
,629471.7%
 
X629471.7%
 
F129160.4%
 
H107350.3%
 
G67800.2%
 
P1654< 0.1%
 
Y1654< 0.1%
 

RELATION ROADWAY
Categorical

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
ON ROADWAY
147648 
OTHER
 
14174
BEYOND SHOULDER - RIGHT
 
2202
SHOULDER
 
2096
BEYOND RIGHT OF WAY
 
975
Other values (4)
 
1617
ValueCountFrequency (%) 
ON ROADWAY14764887.5%
 
OTHER141748.4%
 
BEYOND SHOULDER - RIGHT22021.3%
 
SHOULDER20961.2%
 
BEYOND RIGHT OF WAY9750.6%
 
BEYOND SHOULDER - LEFT8970.5%
 
MEDIAN3690.2%
 
UNKNOWN2590.2%
 
GORE920.1%
 
2020-12-12T20:13:23.093249image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:23.149297image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:23.233370image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length23
Median length10
Mean length9.823948504
Min length4

Overview of Unicode Properties

Unique unicode characters21
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
O32006519.3%
 
A29664017.9%
 
R17028610.3%
 
1598709.6%
 
D1572869.5%
 
N1528689.2%
 
Y1526979.2%
 
W1488829.0%
 
E248011.5%
 
H225461.4%
 
T182481.1%
 
L60920.4%
 
U54540.3%
 
S51950.3%
 
B40740.2%
 
I35460.2%
 
G32690.2%
 
-30990.2%
 
F18720.1%
 
M369< 0.1%
 
K259< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter149444990.2%
 
Space Separator1598709.6%
 
Dash Punctuation30990.2%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
O32006521.4%
 
A29664019.8%
 
R17028611.4%
 
D15728610.5%
 
N15286810.2%
 
Y15269710.2%
 
W14888210.0%
 
E248011.7%
 
H225461.5%
 
T182481.2%
 
L60920.4%
 
U54540.4%
 
S51950.3%
 
B40740.3%
 
I35460.2%
 
G32690.2%
 
F18720.1%
 
M369< 0.1%
 
K259< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
159870100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-3099100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin149444990.2%
 
Common1629699.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
O32006521.4%
 
A29664019.8%
 
R17028611.4%
 
D15728610.5%
 
N15286810.2%
 
Y15269710.2%
 
W14888210.0%
 
E248011.7%
 
H225461.5%
 
T182481.2%
 
L60920.4%
 
U54540.4%
 
S51950.3%
 
B40740.3%
 
I35460.2%
 
G32690.2%
 
F18720.1%
 
M369< 0.1%
 
K259< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
15987098.1%
 
-30991.9%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1657418100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
O32006519.3%
 
A29664017.9%
 
R17028610.3%
 
1598709.6%
 
D1572869.5%
 
N1528689.2%
 
Y1526979.2%
 
W1488829.0%
 
E248011.5%
 
H225461.4%
 
T182481.1%
 
L60920.4%
 
U54540.3%
 
S51950.3%
 
B40740.2%
 
I35460.2%
 
G32690.2%
 
-30990.2%
 
F18720.1%
 
M369< 0.1%
 
K259< 0.1%
 

ACCESS CONTROL
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
NO CONTROL (UNLIMITED ACCESS TO ROADWAY)
133146 
FULL CONTROL (ONLY RAMP ENTRANCE and EXIT)
18374 
PARTIAL CONTROL LIMITED ACCESS TO ROADWAY
 
12054
OTHER
 
4894
UNKNOWN
 
244
ValueCountFrequency (%) 
NO CONTROL (UNLIMITED ACCESS TO ROADWAY)13314678.9%
 
FULL CONTROL (ONLY RAMP ENTRANCE and EXIT)1837410.9%
 
PARTIAL CONTROL LIMITED ACCESS TO ROADWAY120547.1%
 
OTHER48942.9%
 
UNKNOWN2440.1%
 
2020-12-12T20:13:23.314440image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:23.364482image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:23.437546image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length42
Median length40
Mean length39.22625539
Min length5

Overview of Unicode Properties

Unique unicode characters26
Unique unicode categories5 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
83624412.6%
 
O77420611.7%
 
T5076707.7%
 
A4964567.5%
 
N4857207.3%
 
C4723487.1%
 
L3759505.7%
 
R3624705.5%
 
E3504165.3%
 
I3208284.8%
 
D2904004.4%
 
S2904004.4%
 
M1635742.5%
 
Y1635742.5%
 
U1517642.3%
 
(1515202.3%
 
)1515202.3%
 
W1454442.2%
 
P304280.5%
 
F183740.3%
 
a183740.3%
 
n183740.3%
 
d183740.3%
 
X183740.3%
 
H48940.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter542353482.0%
 
Space Separator83624412.6%
 
Open Punctuation1515202.3%
 
Close Punctuation1515202.3%
 
Lowercase Letter551220.8%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
O77420614.3%
 
T5076709.4%
 
A4964569.2%
 
N4857209.0%
 
C4723488.7%
 
L3759506.9%
 
R3624706.7%
 
E3504166.5%
 
I3208285.9%
 
D2904005.4%
 
S2904005.4%
 
M1635743.0%
 
Y1635743.0%
 
U1517642.8%
 
W1454442.7%
 
P304280.6%
 
F183740.3%
 
X183740.3%
 
H48940.1%
 
K244< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
836244100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(151520100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)151520100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
a1837433.3%
 
n1837433.3%
 
d1837433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin547865682.8%
 
Common113928417.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
O77420614.1%
 
T5076709.3%
 
A4964569.1%
 
N4857208.9%
 
C4723488.6%
 
L3759506.9%
 
R3624706.6%
 
E3504166.4%
 
I3208285.9%
 
D2904005.3%
 
S2904005.3%
 
M1635743.0%
 
Y1635743.0%
 
U1517642.8%
 
W1454442.7%
 
P304280.6%
 
F183740.3%
 
a183740.3%
 
n183740.3%
 
d183740.3%
 
X183740.3%
 
H48940.1%
 
K244< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
83624473.4%
 
(15152013.3%
 
)15152013.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII6617940100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
83624412.6%
 
O77420611.7%
 
T5076707.7%
 
A4964567.5%
 
N4857207.3%
 
C4723487.1%
 
L3759505.7%
 
R3624705.5%
 
E3504165.3%
 
I3208284.8%
 
D2904004.4%
 
S2904004.4%
 
M1635742.5%
 
Y1635742.5%
 
U1517642.3%
 
(1515202.3%
 
)1515202.3%
 
W1454442.2%
 
P304280.5%
 
F183740.3%
 
a183740.3%
 
n183740.3%
 
d183740.3%
 
X183740.3%
 
H48940.1%
 

LIGHTING
Categorical

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
DAYLIGHT
127236 
DARK - CONTINUOUS STREET
30824 
DARK - STREET LIGHT AT INTERSECTION ONLY
 
3710
DARK - NO STREET
 
2499
DUSK
 
1567
Other values (3)
 
2876
ValueCountFrequency (%) 
DAYLIGHT12723675.4%
 
DARK - CONTINUOUS STREET3082418.3%
 
DARK - STREET LIGHT AT INTERSECTION ONLY37102.2%
 
DARK - NO STREET24991.5%
 
DUSK15670.9%
 
UNKNOWN15380.9%
 
DAWN7090.4%
 
OTHER6290.4%
 
2020-12-12T20:13:23.519115image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:13:23.571661image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:23.650729image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length40
Median length8
Mean length11.67114965
Min length4

Overview of Unicode Properties

Unique unicode characters19
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
T24759512.6%
 
I1691908.6%
 
A1686888.6%
 
D1665458.5%
 
L1346566.8%
 
H1315756.7%
 
Y1309466.7%
 
G1309466.7%
 
1222296.2%
 
E821154.2%
 
N806004.1%
 
R784054.0%
 
O737343.7%
 
S731343.7%
 
U647533.3%
 
K401382.0%
 
-370331.9%
 
C345341.8%
 
W22470.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter180980191.9%
 
Space Separator1222296.2%
 
Dash Punctuation370331.9%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
T24759513.7%
 
I1691909.3%
 
A1686889.3%
 
D1665459.2%
 
L1346567.4%
 
H1315757.3%
 
Y1309467.2%
 
G1309467.2%
 
E821154.5%
 
N806004.5%
 
R784054.3%
 
O737344.1%
 
S731344.0%
 
U647533.6%
 
K401382.2%
 
C345341.9%
 
W22470.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
122229100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-37033100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin180980191.9%
 
Common1592628.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
T24759513.7%
 
I1691909.3%
 
A1686889.3%
 
D1665459.2%
 
L1346567.4%
 
H1315757.3%
 
Y1309467.2%
 
G1309467.2%
 
E821154.5%
 
N806004.5%
 
R784054.3%
 
O737344.1%
 
S731344.0%
 
U647533.6%
 
K401382.2%
 
C345341.9%
 
W22470.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
12222976.7%
 
-3703323.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1969063100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
T24759512.6%
 
I1691908.6%
 
A1686888.6%
 
D1665458.5%
 
L1346566.8%
 
H1315756.7%
 
Y1309466.7%
 
G1309466.7%
 
1222296.2%
 
E821154.2%
 
N806004.1%
 
R784054.0%
 
O737343.7%
 
S731343.7%
 
U647533.3%
 
K401382.0%
 
-370331.9%
 
C345341.8%
 
W22470.1%
 

GEOLOCATION
Categorical

HIGH CARDINALITY

Distinct32152
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
800 W I10 BATON ROUGE, LA
 
653
9700 AIRLINE HW BATON ROUGE, LA (30.431587, -91.080756)
 
639
2600 COLLEGE DR BATON ROUGE, LA (30.42423, -91.138929)
 
633
4500 ESSEN LN BATON ROUGE, LA (30.406932, -91.102406)
 
547
9100 AIRLINE HW BATON ROUGE, LA (30.442971, -91.088863)
 
486
Other values (32147)
165754 
ValueCountFrequency (%) 
800 W I10 BATON ROUGE, LA6530.4%
 
9700 AIRLINE HW BATON ROUGE, LA (30.431587, -91.080756)6390.4%
 
2600 COLLEGE DR BATON ROUGE, LA (30.42423, -91.138929)6330.4%
 
4500 ESSEN LN BATON ROUGE, LA (30.406932, -91.102406)5470.3%
 
9100 AIRLINE HW BATON ROUGE, LA (30.442971, -91.088863)4860.3%
 
700 E I12 BATON ROUGE, LA4830.3%
 
800 W I10 HW BATON ROUGE, LA4610.3%
 
700 W I10 BATON ROUGE, LA4580.3%
 
500 E I10 BATON ROUGE, LA3950.2%
 
100 E I10 BATON ROUGE, LA3850.2%
 
2400 S SHERWOOD FOREST BL BATON ROUGE, LA (30.428341, -91.056084)3840.2%
 
1000 W I10 BATON ROUGE, LA3690.2%
 
700 W I10 HW BATON ROUGE, LA3680.2%
 
1200 W LEE DR BATON ROUGE, LA3600.2%
 
900 E I10 BATON ROUGE, LA3480.2%
 
7700 AIRLINE HW BATON ROUGE, LA (30.470364, -91.108424)3480.2%
 
10000 AIRLINE HW BATON ROUGE, LA (30.420375, -91.072703)3470.2%
 
100 W I10 BATON ROUGE, LA3400.2%
 
1800 S SHERWOOD FOREST BL BATON ROUGE, LA (30.436585, -91.0575)3390.2%
 
800 E I12 BATON ROUGE, LA3350.2%
 
2300 COLLEGE DR BATON ROUGE, LA (30.427068, -91.137056)3260.2%
 
9300 FLORIDA BL BATON ROUGE, LA (30.454261, -91.085635)3240.2%
 
500 W I10 BATON ROUGE, LA3190.2%
 
2400 S ACADIAN TH BATON ROUGE, LA3120.2%
 
100 LEE DR BATON ROUGE, LA (30.394183, -91.159427)3080.2%
 
Other values (32127)15844593.9%
 
2020-12-12T20:13:23.791850image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique19394 ?
Unique (%)11.5%
2020-12-12T20:13:23.890936image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length74
Median length55
Mean length49.7425198
Min length19

Overview of Unicode Properties

Unique unicode characters45
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
84697110.1%
 
05916807.1%
 
14540835.4%
 
O4423055.3%
 
A4294815.1%
 
R3156293.8%
 
E3154373.8%
 
33150233.8%
 
,3003153.6%
 
3003123.6%
 
L2904583.5%
 
N2871673.4%
 
92838393.4%
 
42811723.4%
 
.2632943.1%
 
T2359722.8%
 
B2069682.5%
 
52001712.4%
 
G1995102.4%
 
U1813582.2%
 
21796702.1%
 
61613241.9%
 
71609291.9%
 
81567521.9%
 
-1325201.6%
 
Other values (20)85982010.2%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter350030541.7%
 
Decimal Number278464333.2%
 
Space Separator84697110.1%
 
Other Punctuation5641976.7%
 
Control3003123.6%
 
Dash Punctuation1325201.6%
 
Open Punctuation1316061.6%
 
Close Punctuation1316061.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
059168021.2%
 
145408316.3%
 
331502311.3%
 
928383910.2%
 
428117210.1%
 
52001717.2%
 
21796706.5%
 
61613245.8%
 
71609295.8%
 
81567525.6%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
846971100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
O44230512.6%
 
A42948112.3%
 
R3156299.0%
 
E3154379.0%
 
L2904588.3%
 
N2871678.2%
 
T2359726.7%
 
B2069685.9%
 
G1995105.7%
 
U1813585.2%
 
I1046883.0%
 
S1033673.0%
 
D949132.7%
 
H715952.0%
 
W642861.8%
 
C352371.0%
 
F333151.0%
 
P207720.6%
 
M185400.5%
 
V183810.5%
 
K143650.4%
 
Y109620.3%
 
J43450.1%
 
X773< 0.1%
 
Q317< 0.1%
 

Most frequent Control characters

ValueCountFrequency (%) 
300312100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,30031553.2%
 
.26329446.7%
 
'5810.1%
 
/7< 0.1%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(131606100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-132520100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)131606100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common489185558.3%
 
Latin350030541.7%
 

Most frequent Common characters

ValueCountFrequency (%) 
84697117.3%
 
059168012.1%
 
14540839.3%
 
33150236.4%
 
,3003156.1%
 
3003126.1%
 
92838395.8%
 
42811725.7%
 
.2632945.4%
 
52001714.1%
 
21796703.7%
 
61613243.3%
 
71609293.3%
 
81567523.2%
 
-1325202.7%
 
(1316062.7%
 
)1316062.7%
 
'581< 0.1%
 
/7< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
O44230512.6%
 
A42948112.3%
 
R3156299.0%
 
E3154379.0%
 
L2904588.3%
 
N2871678.2%
 
T2359726.7%
 
B2069685.9%
 
G1995105.7%
 
U1813585.2%
 
I1046883.0%
 
S1033673.0%
 
D949132.7%
 
H715952.0%
 
W642861.8%
 
C352371.0%
 
F333151.0%
 
P207720.6%
 
M185400.5%
 
V183810.5%
 
K143650.4%
 
Y109620.3%
 
J43450.1%
 
X773< 0.1%
 
Q317< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII8392160100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
84697110.1%
 
05916807.1%
 
14540835.4%
 
O4423055.3%
 
A4294815.1%
 
R3156293.8%
 
E3154373.8%
 
33150233.8%
 
,3003153.6%
 
3003123.6%
 
L2904583.5%
 
N2871673.4%
 
92838393.4%
 
42811723.4%
 
.2632943.1%
 
T2359722.8%
 
B2069682.5%
 
52001712.4%
 
G1995102.4%
 
U1813582.2%
 
21796702.1%
 
61613241.9%
 
71609291.9%
 
81567521.9%
 
-1325201.6%
 
Other values (20)85982010.2%
 

Interactions

2020-12-12T20:13:12.710815image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:12.847933image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:12.982548image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:13.117164image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2020-12-12T20:13:23.963999image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-12T20:13:24.054576image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-12T20:13:24.146155image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-12T20:13:24.261755image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-12-12T20:13:24.438407image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-12-12T20:13:14.102512image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:15.053330image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:16.202820image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:13:16.586149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

FILE#CRASH DATECRASH TIMETOT VEHDISTRICTZONESUBZONESTREET#STREET DIRECTIONSTREET NAMESTREET TYPEFORMATTED STREETOCCURED ONHIT&RUNTRAIN INVOLVEDFATALITYINJURYPEDESTRIANAT INTERSECTIONCLOSEST STREETMANNER OF COLLISIONSURFACE CONDITIONSURFACE TYPEROAD CONDITIONROAD TYPEALIGNMENTPRIMARY FACTORSECOND FACTORWEATHERLOCATION KINDRELATION ROADWAYACCESS CONTROLLIGHTINGGEOLOCATION
017-0000972007/07/201704:00 PM24B18300.0NaNSCENICHW8300 SCENIC HWU.S. HWYNaNNaNNaNNaNNaNXSNIPEREAR ENDDRYCONCRETENO ABNORMALITIESTOW-WAY ROAD WITH A PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSNaNCLEARBUSINESS CONTINUOUSON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT8300 SCENIC HW\nBATON ROUGE, LA\n(30.522869, -91.180446)
117-0001005407/17/201708:44 AM24F14700.0NFOSTERDR4700 N FOSTER DRCITY STREETNaNNaNNaNXNaNXEVANGELINE BLREAR ENDDRYCONCRETENO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSMOVEMENT PRIOR TO CRASHCLEARRESIDENTIAL DISTRICTON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT4700 N FOSTER DR\nBATON ROUGE, LA\n(30.493052, -91.140585)
217-0001001207/16/201702:42 AM13F23700.0NaNLAKE LABERGECT3700 LAKE LABERGE CTCITY STREETNaNNaNNaNNaNNaNXLAKE SHERWOOD AVNON-COLLISION WITH MOTOR VEHICLEDRYBLACK TOPNO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSMOVEMENT PRIOR TO CRASHCLEARRESIDENTIAL DISTRICTON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DARK - CONTINUOUS STREET3700 LAKE LABERGE CT\nBATON ROUGE, LA\n(30.418399, -91.048159)
317-0001003007/16/201704:02 PM22B51100.0EI10HW1100 E I10 HWINTERSTATENaNNaNNaNNaNNaNNaNESSEN LNOTHERWETCONCRETENO ABNORMALITIESONE-WAY ROADSTRAIGHT-LEVELVIOLATIONSNaNRAINMANUFACTURING OF INDUSTRAILON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT1100 E I10 HW\nBATON ROUGE, LA
417-0000998707/15/201703:42 PM22D33700.0NaNPERKINSRD3700 PERKINS RDSTATE HWYNaNNaNNaNNaNNaNNaNACADIAN THLEFT TURNDRYBLACK TOPNO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELMOVEMENT PRIOR TO CRASHNaNCLEARBUSINESS, MIXED RESIDENTIALON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT3700 PERKINS RD\nBATON ROUGE, LA\n(30.420465, -91.151552)
517-0001003507/16/201705:31 PM32E11500.0NaNLEEDR1500 LEE DRCITY STREETXNaNNaNNaNNaNXCYPRESS STREAR ENDWETCONCRETENO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSROAD SURFACECLOUDYRESIDENTIAL DISTRICTON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT1500 LEE DR\nBATON ROUGE, LA\n(30.409073, -91.147989)
617-0000990707/13/201706:17 PM23G27500.0NaNJEFFERSONHW7500 JEFFERSON HWSTATE HWYNaNNaNNaNNaNNaNNaNLOBDELL AVSIDESWIPE SAMEDRYCONCRETENO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELMOVEMENT PRIOR TO CRASHNaNCLOUDYBUSINESS CONTINUOUSON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT7500 JEFFERSON HW\nBATON ROUGE, LA\n(30.433082, -91.110753)
717-0001006207/15/201704:00 AM23E511800.0NaNOLD HAMMONDHW11800 OLD HAMMOND HWSTATE HWYXNaNNaNNaNNaNNaNKING RICHARDRIGHT TURNDRYBLACK TOPNO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSMOVEMENT PRIOR TO CRASHCLEARRESIDENTIAL DISTRICTON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DARK - CONTINUOUS STREET11800 OLD HAMMOND HW\nBATON ROUGE, LA\n(30.438115, -91.052783)
817-0001003107/16/201704:30 PM22B22950.0NaNPERKINSRD2950 PERKINS RDSTATE HWYNaNNaNNaNNaNNaNNaNI10 HWOTHERWETCONCRETENO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSNaNRAINBUSINESS, MIXED RESIDENTIALON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT2950 PERKINS RD\nBATON ROUGE, LA\n(30.425175, -91.158639)
917-0000999907/15/201701:53 PM22C3400.0WLEENaN400 W LEECITY STREETNaNNaNNaNNaNNaNNaNBURBANKREAR ENDDRYCONCRETENO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELCONDITION OF DRIVERNaNCLEARBUSINESS CONTINUOUSON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT400 W LEE\nBATON ROUGE, LA\n(30.391797, -91.161873)

Last rows

FILE#CRASH DATECRASH TIMETOT VEHDISTRICTZONESUBZONESTREET#STREET DIRECTIONSTREET NAMESTREET TYPEFORMATTED STREETOCCURED ONHIT&RUNTRAIN INVOLVEDFATALITYINJURYPEDESTRIANAT INTERSECTIONCLOSEST STREETMANNER OF COLLISIONSURFACE CONDITIONSURFACE TYPEROAD CONDITIONROAD TYPEALIGNMENTPRIMARY FACTORSECOND FACTORWEATHERLOCATION KINDRELATION ROADWAYACCESS CONTROLLIGHTINGGEOLOCATION
16870217-0000975807/09/201702:04 PM23D12300.0NSHERWOOD FORESTDR2300 N SHERWOOD FOREST DRCITY STREETNaNNaNNaNNaNNaNNaNDARRYL DRSIDESWIPE SAMEWETCONCRETENO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSNaNRAINBUSINESS, MIXED RESIDENTIALON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT2300 N SHERWOOD FOREST DR\nBATON ROUGE, LA\n(30.469744, -91.058082)
16870317-0001001407/10/201709:58 AM23E110000.0NaNFLORIDABL10000 FLORIDA BLU.S. HWYNaNNaNNaNNaNNaNXSHARP RDRIGHT ANGLEDRYCONCRETENO ABNORMALITIESTOW-WAY ROAD WITH A PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSNaNCLEARBUSINESS, MIXED RESIDENTIALON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT10000 FLORIDA BL\nBATON ROUGE, LA\n(30.456398, -91.072071)
16870417-0000999207/15/201701:22 PM22E25100.0NaNESSENLN5100 ESSEN LNSTATE HWYNaNNaNNaNNaNNaNNaNHENNESSYRIGHT ANGLEWETCONCRETENO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSNaNRAINMANUFACTURING OF INDUSTRAILON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT5100 ESSEN LN\nBATON ROUGE, LA\n(30.401538, -91.105578)
16870517-0000975407/09/201706:18 PM13A34211.0NSHERWOOD FORESTDR4211 N SHERWOOD FOREST DRCITY STREETNaNNaNNaNXNaNNaNGREENWELL SPRINGS RDOTHERDRYCONCRETENO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSNaNCLEARRESIDENTIAL DISTRICTSHOULDERNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT4211 N SHERWOOD FOREST DR\nBATON ROUGE, LA\n(30.489828, -91.060656)
16870617-0001000207/14/201708:22 PM22B15251.0NaNGOVERNMENTST5251 GOVERNMENT STSTATE HWYNaNNaNNaNNaNNaNXCOMMMUNITY COLLEGE DRREAR ENDWETCONCRETENO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSNaNCLOUDYBUSINESS CONTINUOUSON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DARK - CONTINUOUS STREET5251 GOVERNMENT ST\nBATON ROUGE, LA\n(30.444604, -91.135654)
16870717-0000995307/14/201702:35 PM23G33276.0NaNDRUSILLALN3276 DRUSILLA LNCITY STREETNaNNaNNaNNaNNaNXINTERLINE AVRIGHT TURNDRYBLACK TOPNO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSNaNCLEARBUSINESS CONTINUOUSON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT3276 DRUSILLA LN\nBATON ROUGE, LA\n(30.420651, -91.087938)
16870817-0001001707/14/201711:44 AM23E11000.0NaNSHERWOOD FORESTBL1000 SHERWOOD FOREST BLCITY STREETNaNNaNNaNNaNNaNNaNGOODWOOD BLREAR ENDDRYCONCRETENO ABNORMALITIESTOW-WAY ROAD WITH A PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSNaNCLEARBUSINESS, MIXED RESIDENTIALON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT1000 SHERWOOD FOREST BL\nBATON ROUGE, LA\n(30.448673, -91.058182)
16870917-0000977307/10/201710:23 AM23C19100.0NaNFLORIDABL9100 FLORIDA BLSTATE HWYNaNNaNNaNNaNNaNNaNCENTERWAY BLSIDESWIPE SAMEDRYBLACK TOPNO ABNORMALITIESTOW-WAY ROAD WITH A PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSMOVEMENT PRIOR TO CRASHCLOUDYBUSINESS, MIXED RESIDENTIALON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT9100 FLORIDA BL\nBATON ROUGE, LA\n(30.453633, -91.088852)
16871017-0001002607/15/201705:13 PM24B24599.0NaNHARDINGBL4599 HARDING BLSTATE HWYNaNNaNNaNNaNNaNNaNPLANK RDREAR ENDWETCONCRETENO ABNORMALITIESTOW-WAY ROAD WITH A PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSNaNRAINBUSINESS, MIXED RESIDENTIALON ROADWAYPARTIAL CONTROL LIMITED ACCESS TO ROADWAYDAYLIGHT4599 HARDING BL\nBATON ROUGE, LA\n(30.521773, -91.14619)
16871117-0000993707/14/201711:57 AM21C11400.0NFOSTERDR1400 N FOSTER DRSTATE HWYNaNNaNNaNNaNNaNXGUS YOUNGREAR ENDDRYBLACK TOPNO ABNORMALITIESTWO-WAY ROAD WITH NO PHYSICAL SEPARATIONSTRAIGHT-LEVELVIOLATIONSMOVEMENT PRIOR TO CRASHCLEARBUSINESS, MIXED RESIDENTIALON ROADWAYNO CONTROL (UNLIMITED ACCESS TO ROADWAY)DAYLIGHT1400 N FOSTER DR\nBATON ROUGE, LA\n(30.461731, -91.139401)